Merge commit '0952958af7685646cdbf2a4907c6e2ae59d4d352'

analysis/2026042802-1/2026042802-1_analysis_summary.json

@@ -0,0 +1,21 @@
+{
+  "pcap_path": "D:\\Dev\\Codes\\rvbust-code\\FlyingShotPkg_3.15_VDA\\Rvbust\\uttc-20260428\\2026042802-1.pcap",
+  "all_command_count": 1788,
+  "trigger_count": 17,
+  "existing_runtime_actual_send_exists": true,
+  "existing_runtime_actual_send_has_io_columns": false,
+  "existing_shot_events_exists": true,
+  "pcap_specific_combined_export_preexisting": false,
+  "average_max_error_deg": 4.241583591714439,
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+  "average_rms_error_deg": 2.5406136706026206,
+  "max_error_axis_counter": {
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+  },
+  "order_only_addr_mismatch_count": 14,
+  "real_addr_mismatch_count": 0
+}

analysis/2026042802-1/2026042802-1_j519_trigger_frames.csv

@@ -0,0 +1,18 @@
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analysis/2026042802-1/2026042802-1_status_feedback_summary.json

@@ -0,0 +1,37 @@
+{
+  "pcap_path": "D:\\Dev\\Codes\\rvbust-code\\FlyingShotPkg_3.15_VDA\\Rvbust\\uttc-20260428\\2026042802-1.pcap",
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+  "best_status_max_error_axis_counter": {
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+  },
+  "best_status_delta_from_paired_cycles_counter": {
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+    "9": 9
+  },
+  "best_status_delta_from_trigger_sequence_counter": {
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+  },
+  "best_status_time_after_trigger_ms_min": 71.83799999999962,
+  "best_status_time_after_trigger_ms_max": 79.96399999999859,
+  "best_status_time_after_trigger_ms_avg": 75.6613529411763,
+  "search_window_cycles": 20
+}

analysis/2026042802-1/2026042802-1_trigger_manual_compare.csv

@@ -0,0 +1,18 @@
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analysis/2026042802-1/2026042802-1_trigger_offset_6_7_8_compare.csv

@@ -0,0 +1,18 @@
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analysis/2026042802-1/2026042802-1_trigger_status_feedback_vs_teach_points.csv

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analysis/2026042802-1/2026042802-1_trigger_vs_teach_points.csv

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analysis/analyze_2026042802_1_status_feedback_vs_teach_points.py

@@ -0,0 +1,363 @@
+#!/usr/bin/env python3
+"""提取 2026042802-1 抓包中的 60015 状态反馈，并和 UTTC_MS11 示教点对比。"""
+
+from __future__ import annotations
+
+import csv
+import json
+import math
+import struct
+import subprocess
+from collections import Counter
+from pathlib import Path
+
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+DEFAULT_PCAP = REPO_ROOT.parent / "Rvbust" / "uttc-20260428" / "2026042802-1.pcap"
+DEFAULT_TSHARK = Path(r"D:\Zyx\Downloads\WiresharkPortable32\App\Wireshark\tshark.exe")
+OUTPUT_DIR = REPO_ROOT / "analysis" / "2026042802-1"
+CONFIG_PATH = REPO_ROOT / "Config" / "RobotConfig.json"
+SEARCH_WINDOW_CYCLES = 20
+
+
+def be_u32(data: bytes, offset: int) -> int:
+    """按大端读取 4 字节无符号整数。"""
+    return struct.unpack(">I", data[offset : offset + 4])[0]
+
+
+def be_u16(data: bytes, offset: int) -> int:
+    """按大端读取 2 字节无符号整数。"""
+    return struct.unpack(">H", data[offset : offset + 2])[0]
+
+
+def be_f32(data: bytes, offset: int) -> float:
+    """按大端读取 4 字节浮点数。"""
+    return struct.unpack(">f", data[offset : offset + 4])[0]
+
+
+def load_udp_rows(pcap: Path, tshark: Path) -> list[list[str]]:
+    """提取 UDP 60015 原始字段，后续按方向和长度拆分命令与状态。"""
+    command = [
+        str(tshark),
+        "-r",
+        str(pcap),
+        "-Y",
+        "udp.port==60015",
+        "-T",
+        "fields",
+        "-e",
+        "frame.number",
+        "-e",
+        "frame.time_relative",
+        "-e",
+        "ip.src",
+        "-e",
+        "ip.dst",
+        "-e",
+        "udp.payload",
+    ]
+    output = subprocess.check_output(command, text=True, encoding="utf-8", errors="ignore")
+    rows: list[list[str]] = []
+    for line in output.splitlines():
+        if not line.strip():
+            continue
+        parts = line.split("\t")
+        if len(parts) >= 5:
+            rows.append(parts[:5])
+    return rows
+
+
+def decode_command_records(rows: list[list[str]], client_ip: str, robot_ip: str) -> list[dict]:
+    """把 64B J519 命令帧解码成结构化记录。"""
+    records: list[dict] = []
+    for frame_no, time_rel, ip_src, ip_dst, payload_hex in rows:
+        if ip_src != client_ip or ip_dst != robot_ip:
+            continue
+
+        payload = bytes.fromhex(payload_hex)
+        if len(payload) != 64:
+            continue
+
+        records.append(
+            {
+                "frame_number": int(frame_no),
+                "time_relative_s": float(time_rel),
+                "sequence": be_u32(payload, 0x08),
+                "write_io_value": be_u16(payload, 0x18),
+                "j1_deg": be_f32(payload, 0x1C),
+                "j2_deg": be_f32(payload, 0x20),
+                "j3_deg": be_f32(payload, 0x24),
+                "j4_deg": be_f32(payload, 0x28),
+                "j5_deg": be_f32(payload, 0x2C),
+                "j6_deg": be_f32(payload, 0x30),
+            }
+        )
+    return records
+
+
+def decode_status_records(rows: list[list[str]], client_ip: str, robot_ip: str) -> list[dict]:
+    """把 132B J519 状态帧按运行时代码同口径解码。"""
+    records: list[dict] = []
+    for frame_no, time_rel, ip_src, ip_dst, payload_hex in rows:
+        if ip_src != robot_ip or ip_dst != client_ip:
+            continue
+
+        payload = bytes.fromhex(payload_hex)
+        if len(payload) != 132:
+            continue
+
+        status = payload[0x0C]
+        joints = [be_f32(payload, 0x3C + index * 4) for index in range(6)]
+        pose = [be_f32(payload, 0x18 + index * 4) for index in range(6)]
+        records.append(
+            {
+                "frame_number": int(frame_no),
+                "time_relative_s": float(time_rel),
+                "sequence": be_u32(payload, 0x08),
+                "status": status,
+                "accepts_command": bool(status & 0b0001),
+                "received_command": bool(status & 0b0010),
+                "system_ready": bool(status & 0b0100),
+                "robot_in_motion": bool(status & 0b1000),
+                "read_io_value": be_u16(payload, 0x12),
+                "timestamp": be_u32(payload, 0x14),
+                "pose_x_mm": pose[0],
+                "pose_y_mm": pose[1],
+                "pose_z_mm": pose[2],
+                "pose_w_deg": pose[3],
+                "pose_p_deg": pose[4],
+                "pose_r_deg": pose[5],
+                "j1_deg": joints[0],
+                "j2_deg": joints[1],
+                "j3_deg": joints[2],
+                "j4_deg": joints[3],
+                "j5_deg": joints[4],
+                "j6_deg": joints[5],
+            }
+        )
+    return records
+
+
+def pick_trigger_first_high_frames(records: list[dict]) -> list[dict]:
+    """由于 io_keep_cycles=2，只保留每组高电平脉冲的第一帧。"""
+    trigger_frames: list[dict] = []
+    previous_high = False
+    for record in records:
+        current_high = record["write_io_value"] > 0
+        if current_high and not previous_high:
+            trigger_frames.append(record)
+        previous_high = current_high
+    return trigger_frames
+
+
+def load_uttc_ms11_config() -> dict:
+    """读取 UTTC_MS11 的示教点和触发配置。"""
+    config = json.loads(CONFIG_PATH.read_text(encoding="utf-8"))
+    return config["flying_shots"]["UTTC_MS11"]
+
+
+def build_diff_row(prefix: str, actual_deg: list[float], teach_deg: list[float], row: dict) -> tuple[float, float, str]:
+    """向结果行写入逐轴误差，并返回聚合误差。"""
+    diffs = [actual_deg[index] - teach_deg[index] for index in range(6)]
+    abs_diffs = [abs(value) for value in diffs]
+    max_error = max(abs_diffs)
+    max_error_axis = f"J{abs_diffs.index(max_error) + 1}"
+    rms_error = math.sqrt(sum(value * value for value in diffs) / 6.0)
+
+    for joint_index in range(6):
+        joint_no = joint_index + 1
+        row[f"{prefix}_j{joint_no}_actual_deg"] = actual_deg[joint_index]
+        row[f"{prefix}_diff_j{joint_no}_deg"] = diffs[joint_index]
+
+    row[f"{prefix}_max_error_axis"] = max_error_axis
+    row[f"{prefix}_max_error_deg"] = max_error
+    row[f"{prefix}_rms_error_deg"] = rms_error
+    return max_error, rms_error, max_error_axis
+
+
+def build_trigger_status_rows(trigger_frames: list[dict], status_records: list[dict], shot_config: dict) -> list[dict]:
+    """按触发顺序对齐命令帧、当前状态帧以及最接近示教点的反馈状态帧。"""
+    rows: list[dict] = []
+    trigger_waypoint_indices = [index for index, flag in enumerate(shot_config["shot_flags"]) if flag]
+    status_by_sequence = {record["sequence"]: record for record in status_records}
+    status_sequence_set = set(status_by_sequence)
+
+    for trigger_no, (trigger_frame, waypoint_index) in enumerate(zip(trigger_frames, trigger_waypoint_indices), start=1):
+        teach_deg = [math.degrees(value) for value in shot_config["traj_waypoints"][waypoint_index]]
+        current_status_sequence = trigger_frame["sequence"] - 8
+        current_status = status_by_sequence[current_status_sequence]
+
+        row = {
+            "trigger_no": trigger_no,
+            "waypoint_index": waypoint_index,
+            "trigger_frame_number": trigger_frame["frame_number"],
+            "trigger_time_relative_s": trigger_frame["time_relative_s"],
+            "trigger_sequence": trigger_frame["sequence"],
+            "paired_status_frame_number": current_status["frame_number"],
+            "paired_status_time_relative_s": current_status["time_relative_s"],
+            "paired_status_sequence": current_status["sequence"],
+            "paired_status_timestamp": current_status["timestamp"],
+            "paired_status_to_trigger_sequence_delta": current_status["sequence"] - trigger_frame["sequence"],
+            "paired_status_to_trigger_time_ms": (current_status["time_relative_s"] - trigger_frame["time_relative_s"]) * 1000.0,
+        }
+
+        for joint_index in range(6):
+            joint_no = joint_index + 1
+            row[f"teach_j{joint_no}_deg"] = teach_deg[joint_index]
+
+        build_diff_row(
+            "paired_status",
+            [current_status[f"j{joint_no}_deg"] for joint_no in range(1, 7)],
+            teach_deg,
+            row,
+        )
+
+        best_candidate = None
+        for delta_cycles in range(-SEARCH_WINDOW_CYCLES, SEARCH_WINDOW_CYCLES + 1):
+            candidate_sequence = current_status_sequence + delta_cycles
+            if candidate_sequence not in status_sequence_set:
+                continue
+
+            candidate = status_by_sequence[candidate_sequence]
+            diffs = [candidate[f"j{joint_no}_deg"] - teach_deg[joint_no - 1] for joint_no in range(1, 7)]
+            rms_error = math.sqrt(sum(value * value for value in diffs) / 6.0)
+            max_error = max(abs(value) for value in diffs)
+            score = (rms_error, max_error, abs(delta_cycles))
+            if best_candidate is None or score < best_candidate["score"]:
+                best_candidate = {
+                    "score": score,
+                    "delta_cycles": delta_cycles,
+                    "record": candidate,
+                }
+
+        if best_candidate is None:
+            raise RuntimeError(f"Trigger {trigger_no} 未找到候选状态帧。")
+
+        best_status = best_candidate["record"]
+        row["best_status_frame_number"] = best_status["frame_number"]
+        row["best_status_time_relative_s"] = best_status["time_relative_s"]
+        row["best_status_sequence"] = best_status["sequence"]
+        row["best_status_timestamp"] = best_status["timestamp"]
+        row["best_status_delta_from_paired_cycles"] = best_candidate["delta_cycles"]
+        row["best_status_delta_from_trigger_sequence"] = best_status["sequence"] - trigger_frame["sequence"]
+        row["best_status_time_after_trigger_ms"] = (best_status["time_relative_s"] - trigger_frame["time_relative_s"]) * 1000.0
+
+        build_diff_row(
+            "best_status",
+            [best_status[f"j{joint_no}_deg"] for joint_no in range(1, 7)],
+            teach_deg,
+            row,
+        )
+
+        rows.append(row)
+
+    return rows
+
+
+def write_csv(path: Path, rows: list[dict]) -> None:
+    """把分析结果落成 UTF-8 CSV。"""
+    if not rows:
+        raise ValueError(f"No rows to write: {path}")
+
+    path.parent.mkdir(parents=True, exist_ok=True)
+    with path.open("w", newline="", encoding="utf-8") as handle:
+        writer = csv.DictWriter(handle, fieldnames=list(rows[0].keys()))
+        writer.writeheader()
+        writer.writerows(rows)
+
+
+def build_summary(command_records: list[dict], trigger_status_rows: list[dict]) -> dict:
+    """汇总命令序列偏移和状态反馈误差分布。"""
+    sequence_offsets = [row["trigger_sequence"] - row["paired_status_sequence"] for row in trigger_status_rows]
+    best_paired_cycle_offsets = [row["best_status_delta_from_paired_cycles"] for row in trigger_status_rows]
+    best_trigger_sequence_offsets = [row["best_status_delta_from_trigger_sequence"] for row in trigger_status_rows]
+    best_time_offsets = [row["best_status_time_after_trigger_ms"] for row in trigger_status_rows]
+    paired_max_errors = [row["paired_status_max_error_deg"] for row in trigger_status_rows]
+    best_max_errors = [row["best_status_max_error_deg"] for row in trigger_status_rows]
+    paired_axes = Counter(row["paired_status_max_error_axis"] for row in trigger_status_rows)
+    best_axes = Counter(row["best_status_max_error_axis"] for row in trigger_status_rows)
+
+    sequence_offset_counter = Counter()
+    trigger_frames = pick_trigger_first_high_frames(command_records)
+    status_pairs = {row["trigger_frame_number"]: row for row in trigger_status_rows}
+    for trigger_frame in trigger_frames:
+        sequence_offset_counter[trigger_frame["sequence"] - status_pairs[trigger_frame["frame_number"]]["paired_status_sequence"]] += 1
+
+    return {
+        "pcap_path": str(DEFAULT_PCAP),
+        "command_count": len(command_records),
+        "trigger_count": len(trigger_status_rows),
+        "command_minus_paired_status_sequence_counter": dict(sequence_offset_counter),
+        "paired_status_average_max_error_deg": sum(paired_max_errors) / len(paired_max_errors),
+        "paired_status_max_error_deg": max(paired_max_errors),
+        "paired_status_max_error_axis_counter": dict(paired_axes),
+        "best_status_average_max_error_deg": sum(best_max_errors) / len(best_max_errors),
+        "best_status_max_error_deg": max(best_max_errors),
+        "best_status_max_error_axis_counter": dict(best_axes),
+        "best_status_delta_from_paired_cycles_counter": dict(Counter(best_paired_cycle_offsets)),
+        "best_status_delta_from_trigger_sequence_counter": dict(Counter(best_trigger_sequence_offsets)),
+        "best_status_time_after_trigger_ms_min": min(best_time_offsets),
+        "best_status_time_after_trigger_ms_max": max(best_time_offsets),
+        "best_status_time_after_trigger_ms_avg": sum(best_time_offsets) / len(best_time_offsets),
+        "search_window_cycles": SEARCH_WINDOW_CYCLES,
+    }
+
+
+def build_manual_compare_rows(trigger_status_rows: list[dict]) -> list[dict]:
+    """整理成便于人工逐点核对的三时刻对照表。"""
+    rows: list[dict] = []
+    for row in trigger_status_rows:
+        rows.append(
+            {
+                "trigger_no": row["trigger_no"],
+                "waypoint_index": row["waypoint_index"],
+                "trigger_command_sequence": row["trigger_sequence"],
+                "trigger_command_frame": row["trigger_frame_number"],
+                "trigger_command_time_relative_s": row["trigger_time_relative_s"],
+                "trigger_current_status_sequence": row["paired_status_sequence"],
+                "trigger_current_status_frame": row["paired_status_frame_number"],
+                "trigger_current_status_time_relative_s": row["paired_status_time_relative_s"],
+                "command_leads_status_cycles": row["trigger_sequence"] - row["paired_status_sequence"],
+                "trigger_current_status_max_error_axis": row["paired_status_max_error_axis"],
+                "trigger_current_status_max_error_deg": row["paired_status_max_error_deg"],
+                "trigger_current_status_rms_error_deg": row["paired_status_rms_error_deg"],
+                "best_status_sequence": row["best_status_sequence"],
+                "best_status_frame": row["best_status_frame_number"],
+                "best_status_time_relative_s": row["best_status_time_relative_s"],
+                "best_status_delay_from_current_status_cycles": row["best_status_delta_from_paired_cycles"],
+                "best_status_delay_from_trigger_command_cycles": row["best_status_delta_from_trigger_sequence"],
+                "best_status_delay_from_trigger_command_ms": row["best_status_time_after_trigger_ms"],
+                "best_status_max_error_axis": row["best_status_max_error_axis"],
+                "best_status_max_error_deg": row["best_status_max_error_deg"],
+                "best_status_rms_error_deg": row["best_status_rms_error_deg"],
+            }
+        )
+    return rows
+
+
+def main() -> None:
+    """执行状态反馈提取、触发对齐和摘要落盘。"""
+    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+    rows = load_udp_rows(DEFAULT_PCAP, DEFAULT_TSHARK)
+    command_records = decode_command_records(rows, client_ip="192.168.10.10", robot_ip="192.168.10.11")
+    status_records = decode_status_records(rows, client_ip="192.168.10.10", robot_ip="192.168.10.11")
+    trigger_frames = pick_trigger_first_high_frames(command_records)
+    shot_config = load_uttc_ms11_config()
+    trigger_status_rows = build_trigger_status_rows(trigger_frames, status_records, shot_config)
+    manual_compare_rows = build_manual_compare_rows(trigger_status_rows)
+    summary = build_summary(command_records, trigger_status_rows)
+
+    write_csv(OUTPUT_DIR / "2026042802-1_j519_status_feedback_all.csv", status_records)
+    write_csv(OUTPUT_DIR / "2026042802-1_trigger_status_feedback_vs_teach_points.csv", trigger_status_rows)
+    write_csv(OUTPUT_DIR / "2026042802-1_trigger_manual_compare.csv", manual_compare_rows)
+    (OUTPUT_DIR / "2026042802-1_status_feedback_summary.json").write_text(
+        json.dumps(summary, ensure_ascii=False, indent=2),
+        encoding="utf-8",
+    )
+
+    print(json.dumps(summary, ensure_ascii=False, indent=2))
+
+
+if __name__ == "__main__":
+    main()

analysis/analyze_2026042802_1_trigger_vs_teach_points.py

@@ -0,0 +1,250 @@
+#!/usr/bin/env python3
+"""提取 2026042802-1 抓包中的真实 J519 发包，并对比 UTTC_MS11 示教点。"""
+
+from __future__ import annotations
+
+import csv
+import json
+import math
+import struct
+import subprocess
+from collections import Counter
+from pathlib import Path
+
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+DEFAULT_PCAP = REPO_ROOT.parent / "Rvbust" / "uttc-20260428" / "2026042802-1.pcap"
+DEFAULT_TSHARK = Path(r"D:\Zyx\Downloads\WiresharkPortable32\App\Wireshark\tshark.exe")
+OUTPUT_DIR = REPO_ROOT / "analysis" / "2026042802-1"
+CONFIG_PATH = REPO_ROOT / "Config" / "RobotConfig.json"
+RUNTIME_DATA_DIR = REPO_ROOT / "Config" / "Data" / "UTTC_MS11"
+
+
+def be_u32(data: bytes, offset: int) -> int:
+    """按大端读取 4 字节无符号整数。"""
+    return struct.unpack(">I", data[offset : offset + 4])[0]
+
+
+def be_u16(data: bytes, offset: int) -> int:
+    """按大端读取 2 字节无符号整数。"""
+    return struct.unpack(">H", data[offset : offset + 2])[0]
+
+
+def be_f32(data: bytes, offset: int) -> float:
+    """按大端读取 4 字节浮点数。"""
+    return struct.unpack(">f", data[offset : offset + 4])[0]
+
+
+def load_j519_command_rows(pcap: Path, tshark: Path) -> list[list[str]]:
+    """只提取 UDP 60015 的原始字段，后续再按 IP 方向筛选真实下发命令。"""
+    command = [
+        str(tshark),
+        "-r",
+        str(pcap),
+        "-Y",
+        "udp.port==60015",
+        "-T",
+        "fields",
+        "-e",
+        "frame.number",
+        "-e",
+        "frame.time_relative",
+        "-e",
+        "ip.src",
+        "-e",
+        "udp.srcport",
+        "-e",
+        "ip.dst",
+        "-e",
+        "udp.dstport",
+        "-e",
+        "udp.payload",
+    ]
+    output = subprocess.check_output(command, text=True, encoding="utf-8", errors="ignore")
+    rows: list[list[str]] = []
+    for line in output.splitlines():
+        if not line.strip():
+            continue
+        parts = line.split("\t")
+        if len(parts) >= 7:
+            rows.append(parts[:7])
+    return rows
+
+
+def decode_command_records(rows: list[list[str]], client_ip: str, robot_ip: str) -> list[dict]:
+    """把抓包中的 64B J519 命令帧解码成带 IO 信息的结构化记录。"""
+    records: list[dict] = []
+    for frame_no, time_rel, ip_src, _udp_src, ip_dst, _udp_dst, payload_hex in rows:
+        if ip_src != client_ip or ip_dst != robot_ip:
+            continue
+
+        payload = bytes.fromhex(payload_hex)
+        if len(payload) != 64:
+            continue
+
+        io_value = be_u16(payload, 0x18)
+        io_addrs = [bit + 1 for bit in range(16) if io_value & (1 << bit)]
+        targets = [be_f32(payload, 0x1C + index * 4) for index in range(9)]
+        records.append(
+            {
+                "frame_number": int(frame_no),
+                "time_relative_s": float(time_rel),
+                "sequence": be_u32(payload, 0x08),
+                "last_data": payload[0x0C],
+                "write_io_type": payload[0x13],
+                "write_io_index": be_u16(payload, 0x14),
+                "write_io_mask": be_u16(payload, 0x16),
+                "write_io_value": io_value,
+                "io_addrs": io_addrs,
+                "j1_deg": targets[0],
+                "j2_deg": targets[1],
+                "j3_deg": targets[2],
+                "j4_deg": targets[3],
+                "j5_deg": targets[4],
+                "j6_deg": targets[5],
+                "ext1_deg": targets[6],
+                "ext2_deg": targets[7],
+                "ext3_deg": targets[8],
+            }
+        )
+    return records
+
+
+def pick_trigger_first_high_frames(records: list[dict]) -> list[dict]:
+    """由于 io_keep_cycles=2，只记录每组高电平脉冲的第一帧。"""
+    trigger_frames: list[dict] = []
+    previous_high = False
+    for record in records:
+        current_high = record["write_io_value"] > 0
+        if current_high and not previous_high:
+            trigger_frames.append(record)
+        previous_high = current_high
+    return trigger_frames
+
+
+def load_uttc_ms11_config() -> dict:
+    """读取 UTTC_MS11 的示教点和触发配置。"""
+    config = json.loads(CONFIG_PATH.read_text(encoding="utf-8"))
+    return config["flying_shots"]["UTTC_MS11"]
+
+
+def build_trigger_vs_teach_rows(trigger_frames: list[dict], shot_config: dict) -> list[dict]:
+    """按 shot_flags 为 true 的 waypoint 顺序，对齐抓包触发帧和示教点。"""
+    rows: list[dict] = []
+    trigger_waypoint_indices = [index for index, flag in enumerate(shot_config["shot_flags"]) if flag]
+
+    for trigger_no, (frame, waypoint_index) in enumerate(zip(trigger_frames, trigger_waypoint_indices), start=1):
+        teach_rad = shot_config["traj_waypoints"][waypoint_index]
+        teach_deg = [math.degrees(value) for value in teach_rad]
+        actual_deg = [frame[f"j{joint_index}_deg"] for joint_index in range(1, 7)]
+        diffs = [actual_deg[index] - teach_deg[index] for index in range(6)]
+        abs_diffs = [abs(value) for value in diffs]
+        max_error = max(abs_diffs)
+        max_error_axis = f"J{abs_diffs.index(max_error) + 1}"
+        rms_error = math.sqrt(sum(value * value for value in diffs) / 6.0)
+
+        row = {
+            "trigger_no": trigger_no,
+            "waypoint_index": waypoint_index,
+            "frame_number": frame["frame_number"],
+            "sequence": frame["sequence"],
+            "time_relative_s": frame["time_relative_s"],
+            "write_io_value": frame["write_io_value"],
+            "io_addrs": frame["io_addrs"],
+            "config_addr": shot_config["addr"][waypoint_index],
+            "max_error_axis": max_error_axis,
+            "max_error_deg": max_error,
+            "rms_error_deg": rms_error,
+        }
+
+        for joint_index in range(6):
+            joint_no = joint_index + 1
+            row[f"j{joint_no}_actual_deg"] = actual_deg[joint_index]
+            row[f"j{joint_no}_teach_deg"] = teach_deg[joint_index]
+            row[f"diff_j{joint_no}_deg"] = diffs[joint_index]
+
+        rows.append(row)
+
+    return rows
+
+
+def write_csv(path: Path, rows: list[dict]) -> None:
+    """把分析结果落成 UTF-8 CSV，便于后续继续筛选和画图。"""
+    if not rows:
+        raise ValueError(f"No rows to write: {path}")
+
+    serializable_rows: list[dict] = []
+    for row in rows:
+        serializable_row: dict = {}
+        for key, value in row.items():
+            if isinstance(value, list):
+                serializable_row[key] = json.dumps(value, ensure_ascii=False)
+            else:
+                serializable_row[key] = value
+        serializable_rows.append(serializable_row)
+
+    path.parent.mkdir(parents=True, exist_ok=True)
+    with path.open("w", newline="", encoding="utf-8") as handle:
+        writer = csv.DictWriter(handle, fieldnames=list(serializable_rows[0].keys()))
+        writer.writeheader()
+        writer.writerows(serializable_rows)
+
+
+def build_summary(records: list[dict], trigger_rows: list[dict]) -> dict:
+    """汇总本次分析关心的导出状态和误差统计。"""
+    max_errors = [float(row["max_error_deg"]) for row in trigger_rows]
+    rms_errors = [float(row["rms_error_deg"]) for row in trigger_rows]
+    axis_counter = Counter(str(row["max_error_axis"]) for row in trigger_rows)
+
+    order_only_addr_mismatch = 0
+    real_addr_mismatch = 0
+    for row in trigger_rows:
+        io_addrs = list(row["io_addrs"])
+        config_addr = list(row["config_addr"])
+        if io_addrs != config_addr:
+            if sorted(io_addrs) == sorted(config_addr):
+                order_only_addr_mismatch += 1
+            else:
+                real_addr_mismatch += 1
+
+    return {
+        "pcap_path": str(DEFAULT_PCAP),
+        "all_command_count": len(records),
+        "trigger_count": len(trigger_rows),
+        "existing_runtime_actual_send_exists": (RUNTIME_DATA_DIR / "ActualSendJointTraj.txt").exists(),
+        "existing_runtime_actual_send_has_io_columns": False,
+        "existing_shot_events_exists": (RUNTIME_DATA_DIR / "ShotEvents.json").exists(),
+        "pcap_specific_combined_export_preexisting": False,
+        "average_max_error_deg": sum(max_errors) / len(max_errors),
+        "max_error_deg": max(max_errors),
+        "average_rms_error_deg": sum(rms_errors) / len(rms_errors),
+        "max_error_axis_counter": dict(axis_counter),
+        "order_only_addr_mismatch_count": order_only_addr_mismatch,
+        "real_addr_mismatch_count": real_addr_mismatch,
+    }
+
+
+def main() -> None:
+    """执行抓包提取、示教点对齐、CSV 导出和摘要落盘。"""
+    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+    rows = load_j519_command_rows(DEFAULT_PCAP, DEFAULT_TSHARK)
+    records = decode_command_records(rows, client_ip="192.168.10.10", robot_ip="192.168.10.11")
+    trigger_frames = pick_trigger_first_high_frames(records)
+    shot_config = load_uttc_ms11_config()
+    trigger_rows = build_trigger_vs_teach_rows(trigger_frames, shot_config)
+    summary = build_summary(records, trigger_rows)
+
+    write_csv(OUTPUT_DIR / "2026042802-1_j519_actual_send_all_with_io.csv", records)
+    write_csv(OUTPUT_DIR / "2026042802-1_j519_trigger_frames.csv", trigger_frames)
+    write_csv(OUTPUT_DIR / "2026042802-1_trigger_vs_teach_points.csv", trigger_rows)
+    (OUTPUT_DIR / "2026042802-1_analysis_summary.json").write_text(
+        json.dumps(summary, ensure_ascii=False, indent=2),
+        encoding="utf-8",
+    )
+
+    print(json.dumps(summary, ensure_ascii=False, indent=2))
+
+
+if __name__ == "__main__":
+    main()

analysis/build_trigger_offset_compare_6_7_8.py

@@ -0,0 +1,137 @@
+#!/usr/bin/env python3
+"""生成 2026042802-1 抓包中触发偏移 6/7/8 周期的对照表。"""
+
+from __future__ import annotations
+
+import csv
+import json
+import math
+from pathlib import Path
+
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+OUTPUT_DIR = REPO_ROOT / "analysis" / "2026042802-1"
+CONFIG_PATH = REPO_ROOT / "Config" / "RobotConfig.json"
+ACTUAL_SEND_CSV = OUTPUT_DIR / "2026042802-1_j519_actual_send_all_with_io.csv"
+TRIGGER_CSV = OUTPUT_DIR / "2026042802-1_j519_trigger_frames.csv"
+OUTPUT_CSV = OUTPUT_DIR / "2026042802-1_trigger_offset_6_7_8_compare.csv"
+OUTPUT_JSON = OUTPUT_DIR / "2026042802-1_trigger_offset_6_7_8_summary.json"
+
+
+def load_rows(path: Path) -> list[dict]:
+    with path.open(encoding="utf-8") as handle:
+        return list(csv.DictReader(handle))
+
+
+def to_float_list(record: dict, prefix: str = "j") -> list[float]:
+    return [float(record[f"{prefix}{index}_deg"]) for index in range(1, 7)]
+
+
+def compute_diff_metrics(actual_deg: list[float], teach_deg: list[float]) -> tuple[list[float], float, float, str]:
+    diffs = [actual_deg[index] - teach_deg[index] for index in range(6)]
+    abs_diffs = [abs(value) for value in diffs]
+    max_error = max(abs_diffs)
+    rms_error = math.sqrt(sum(value * value for value in diffs) / 6.0)
+    max_axis = f"J{abs_diffs.index(max_error) + 1}"
+    return diffs, max_error, rms_error, max_axis
+
+
+def main() -> None:
+    actual_rows = load_rows(ACTUAL_SEND_CSV)
+    trigger_rows = load_rows(TRIGGER_CSV)
+    config = json.loads(CONFIG_PATH.read_text(encoding="utf-8"))["flying_shots"]["UTTC_MS11"]
+    trigger_waypoint_indices = [index for index, flag in enumerate(config["shot_flags"]) if flag]
+
+    actual_index_by_frame = {int(row["frame_number"]): row for row in actual_rows}
+    actual_order_by_frame = {int(row["frame_number"]): idx for idx, row in enumerate(actual_rows)}
+
+    output_rows: list[dict] = []
+    offset_win_counts = {6: 0, 7: 0, 8: 0}
+
+    for trigger_no, (trigger_row, waypoint_index) in enumerate(zip(trigger_rows, trigger_waypoint_indices), start=1):
+        trigger_frame = int(trigger_row["frame_number"])
+        trigger_order = actual_order_by_frame[trigger_frame]
+        teach_deg = [math.degrees(value) for value in config["traj_waypoints"][waypoint_index]]
+
+        window_start = max(0, trigger_order - 20)
+        window_end = min(len(actual_rows) - 1, trigger_order + 20)
+        best_order = trigger_order
+        best_rms = float("inf")
+        best_max = float("inf")
+
+        for candidate_order in range(window_start, window_end + 1):
+            candidate = actual_rows[candidate_order]
+            _, max_error, rms_error, _ = compute_diff_metrics(to_float_list(candidate), teach_deg)
+            score = (rms_error, max_error, abs(candidate_order - trigger_order))
+            if (best_rms, best_max, abs(best_order - trigger_order)) > score:
+                best_order = candidate_order
+                best_rms = rms_error
+                best_max = max_error
+
+        row = {
+            "trigger_no": trigger_no,
+            "waypoint_index": waypoint_index,
+            "best_sample_order": best_order,
+            "best_frame_number": int(actual_rows[best_order]["frame_number"]),
+            "best_sequence": int(actual_rows[best_order]["sequence"]),
+            "best_time_relative_s": float(actual_rows[best_order]["time_relative_s"]),
+        }
+
+        for joint_index in range(6):
+            row[f"teach_j{joint_index + 1}_deg"] = teach_deg[joint_index]
+
+        for offset in (6, 7, 8):
+            target_order = min(len(actual_rows) - 1, best_order + offset)
+            target = actual_rows[target_order]
+            actual_deg = to_float_list(target)
+            diffs, max_error, rms_error, max_axis = compute_diff_metrics(actual_deg, teach_deg)
+
+            row[f"offset_{offset}_frame_number"] = int(target["frame_number"])
+            row[f"offset_{offset}_sequence"] = int(target["sequence"])
+            row[f"offset_{offset}_time_relative_s"] = float(target["time_relative_s"])
+            row[f"offset_{offset}_max_error_axis"] = max_axis
+            row[f"offset_{offset}_max_error_deg"] = max_error
+            row[f"offset_{offset}_rms_error_deg"] = rms_error
+            row[f"offset_{offset}_delta_from_best_ms"] = (
+                float(target["time_relative_s"]) - float(actual_rows[best_order]["time_relative_s"])
+            ) * 1000.0
+            for joint_index in range(6):
+                joint_no = joint_index + 1
+                row[f"offset_{offset}_j{joint_no}_actual_deg"] = actual_deg[joint_index]
+                row[f"offset_{offset}_diff_j{joint_no}_deg"] = diffs[joint_index]
+
+        best_offset = min(
+            (6, 7, 8),
+            key=lambda offset: (
+                row[f"offset_{offset}_rms_error_deg"],
+                row[f"offset_{offset}_max_error_deg"],
+            ),
+        )
+        row["best_of_6_7_8_offset"] = best_offset
+        offset_win_counts[best_offset] += 1
+        output_rows.append(row)
+
+    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+    with OUTPUT_CSV.open("w", newline="", encoding="utf-8") as handle:
+        writer = csv.DictWriter(handle, fieldnames=list(output_rows[0].keys()))
+        writer.writeheader()
+        writer.writerows(output_rows)
+
+    summary = {
+        "rows": len(output_rows),
+        "best_offset_win_counts": offset_win_counts,
+        "average_max_error_deg": {
+            str(offset): sum(row[f"offset_{offset}_max_error_deg"] for row in output_rows) / len(output_rows)
+            for offset in (6, 7, 8)
+        },
+        "average_rms_error_deg": {
+            str(offset): sum(row[f"offset_{offset}_rms_error_deg"] for row in output_rows) / len(output_rows)
+            for offset in (6, 7, 8)
+        },
+    }
+    OUTPUT_JSON.write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding="utf-8")
+    print(json.dumps(summary, ensure_ascii=False, indent=2))
+
+
+if __name__ == "__main__":
+    main()

analysis/calc_jointdetail_acceleration.py

@@ -0,0 +1,461 @@
+#!/usr/bin/env python3
+"""计算 JointDetialTraj 类文件的速度 / 加速度 / 跃度峰值，并与当前生效轴限位对比。
+
+输入格式:
+    time joint1 joint2 ... jointN
+
+本脚本采用的规则:
+1. 将轨迹按离散时间采样点读取，允许时间轴非等间隔。
+2. 自动推断角度单位:
+   - 任一关节绝对值超过 2*pi*1.5，则按 degree 处理
+   - 否则按 radian 处理
+3. 使用后向差分计算导数:
+      v_i = (q_i - q_{i-1}) / dt_i
+      a_i = (v_i - v_{i-1}) / dt_i
+      j_i = (a_i - a_{i-1}) / dt_i
+4. 所有导数量统一换算成 rad 基单位，再与当前生效的机器人限值比较。
+
+当前生效限值来源:
+    .robot limit.velocity
+    .robot limit.acceleration * RobotConfig.robot.acc_limit
+    .robot limit.jerk * RobotConfig.robot.jerk_limit
+"""
+
+from __future__ import annotations
+
+import argparse
+import math
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Iterable
+
+
+AUTO_DEG_THRESHOLD = 2.0 * math.pi * 1.5
+DEFAULT_VELOCITY_LIMITS = [6.45, 5.41, 7.15, 9.59, 9.51, 17.45]
+DEFAULT_ACCELERATION_LIMITS = [26.90, 22.54, 29.81, 39.99, 39.63, 72.72]
+DEFAULT_JERK_LIMITS = [224.22, 187.86, 248.46, 333.30, 330.27, 606.01]
+DEFAULT_JOINT_NAMES = [f"Joint{index}" for index in range(1, 7)]
+
+
+@dataclass(frozen=True)
+class JointLimit:
+    name: str
+    velocity: float
+    acceleration: float
+    jerk: float
+
+
+@dataclass(frozen=True)
+class PeakMetric:
+    joint_name: str
+    axis_index: int
+    window_start: float
+    window_end: float
+    row_number: int
+    metric_native: float
+    metric_rad: float
+    effective_limit_rad: float
+
+    @property
+    def ratio_vs_limit(self) -> float:
+        return abs(self.metric_rad) / self.effective_limit_rad
+
+
+@dataclass(frozen=True)
+class EffectiveLimits:
+    joints: list[JointLimit]
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description="Calculate velocity / acceleration / jerk peaks from JointDetialTraj.txt and compare with built-in effective robot limits."
+    )
+    parser.add_argument("joint_detail", type=Path, help="Path to JointDetialTraj.txt")
+    parser.add_argument(
+        "--limit-csv",
+        type=Path,
+        default=None,
+        help="Optional CSV file with columns: Joint,Velocity,Acceleration,Jerk . If omitted, use built-in 1/1 effective limits.",
+    )
+    parser.add_argument(
+        "--unit",
+        choices=("auto", "rad", "deg"),
+        default="auto",
+        help="Input joint-angle unit. Default: auto.",
+    )
+    return parser.parse_args()
+
+
+def resolve_path(path: Path) -> Path:
+    return path if path.is_absolute() else (Path.cwd() / path).resolve()
+
+
+def read_joint_rows(path: Path) -> list[list[float]]:
+    rows: list[list[float]] = []
+    for raw_line in path.read_text(encoding="utf-8").splitlines():
+        line = raw_line.strip()
+        if not line:
+            continue
+        rows.append([float(part) for part in line.split()])
+
+    if len(rows) < 4:
+        raise ValueError(f"{path} must contain at least 4 rows to calculate jerk.")
+
+    width = len(rows[0])
+    if width < 3:
+        raise ValueError(f"{path} must contain time + at least 2 joint columns.")
+
+    for index, row in enumerate(rows, start=1):
+        if len(row) != width:
+            raise ValueError(f"{path} line {index} has inconsistent column count.")
+
+    return rows
+
+
+def trim_rows_to_limit_count(rows: list[list[float]], limit_count: int) -> tuple[list[list[float]], str | None]:
+    joint_count = len(rows[0]) - 1
+    if joint_count == limit_count:
+        return rows, None
+
+    if joint_count < limit_count:
+        raise ValueError(f"Joint column count ({joint_count}) is smaller than robot limit count ({limit_count}).")
+
+    trimmed_rows = [row[: limit_count + 1] for row in rows]
+    ignored_joint_count = joint_count - limit_count
+    trim_note = (
+        f"ignored_joint_columns={ignored_joint_count} "
+        f"(using first {limit_count} joints out of {joint_count}; trailing columns treated as external axes/placeholders)"
+    )
+    return trimmed_rows, trim_note
+
+
+def infer_unit(rows: Iterable[list[float]], requested_unit: str) -> str:
+    if requested_unit != "auto":
+        return requested_unit
+
+    max_abs_joint = max(abs(value) for row in rows for value in row[1:])
+    return "deg" if max_abs_joint > AUTO_DEG_THRESHOLD else "rad"
+
+
+def read_limit_csv(path: Path) -> list[JointLimit]:
+    rows = [line.strip() for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]
+    if len(rows) < 2:
+        raise ValueError(f"{path} must contain a header and at least one data row.")
+
+    header = [part.strip().lower() for part in rows[0].split(",")]
+    expected = ["joint", "velocity", "acceleration", "jerk"]
+    if header != expected:
+        raise ValueError(f"{path} header must be: Joint,Velocity,Acceleration,Jerk")
+
+    limits: list[JointLimit] = []
+    for row_index, row in enumerate(rows[1:], start=2):
+        parts = [part.strip() for part in row.split(",")]
+        if len(parts) != 4:
+            raise ValueError(f"{path} line {row_index} must contain 4 columns.")
+        limits.append(
+            JointLimit(
+                name=parts[0],
+                velocity=float(parts[1]),
+                acceleration=float(parts[2]),
+                jerk=float(parts[3]),
+            )
+        )
+    return limits
+
+
+def load_effective_limits(limit_csv_path: Path | None) -> EffectiveLimits:
+    if limit_csv_path is not None:
+        limits = read_limit_csv(resolve_path(limit_csv_path))
+    else:
+        limits = [
+            JointLimit(
+                name=name,
+                velocity=velocity,
+                acceleration=acceleration,
+                jerk=jerk,
+            )
+            for name, velocity, acceleration, jerk in zip(
+                DEFAULT_JOINT_NAMES,
+                DEFAULT_VELOCITY_LIMITS,
+                DEFAULT_ACCELERATION_LIMITS,
+                DEFAULT_JERK_LIMITS,
+                strict=True,
+            )
+        ]
+
+    return EffectiveLimits(joints=limits)
+
+
+def to_radians(value: float, unit: str) -> float:
+    return math.radians(value) if unit == "deg" else value
+
+
+def to_native_from_rad(value: float, unit: str) -> float:
+    return math.degrees(value) if unit == "deg" else value
+
+
+def calculate_velocity_peaks(rows: list[list[float]], unit: str, limits: list[JointLimit]) -> list[PeakMetric]:
+    joint_count = len(rows[0]) - 1
+    if joint_count != len(limits):
+        raise ValueError(f"Joint column count ({joint_count}) does not match robot limit count ({len(limits)}).")
+
+    peaks: list[PeakMetric | None] = [None] * joint_count
+
+    for row_index in range(1, len(rows)):
+        previous = rows[row_index - 1]
+        current = rows[row_index]
+        dt = current[0] - previous[0]
+        if dt <= 0.0:
+            raise ValueError(f"Non-positive dt at line {row_index + 1}: {dt}")
+
+        for joint_index in range(joint_count):
+            dq_native = current[joint_index + 1] - previous[joint_index + 1]
+            dq_rad = to_radians(dq_native, unit)
+            velocity_rad = dq_rad / dt
+            velocity_native = to_native_from_rad(velocity_rad, unit)
+
+            candidate = PeakMetric(
+                joint_name=limits[joint_index].name,
+                axis_index=joint_index + 1,
+                window_start=previous[0],
+                window_end=current[0],
+                row_number=row_index + 1,
+                metric_native=velocity_native,
+                metric_rad=velocity_rad,
+                effective_limit_rad=limits[joint_index].velocity,
+            )
+
+            current_peak = peaks[joint_index]
+            if current_peak is None or abs(candidate.metric_rad) > abs(current_peak.metric_rad):
+                peaks[joint_index] = candidate
+
+    return [peak for peak in peaks if peak is not None]
+
+
+def calculate_acceleration_peaks(rows: list[list[float]], unit: str, limits: list[JointLimit]) -> list[PeakMetric]:
+    joint_count = len(rows[0]) - 1
+    if joint_count != len(limits):
+        raise ValueError(f"Joint column count ({joint_count}) does not match robot limit count ({len(limits)}).")
+
+    velocities_rad: list[list[float]] = []
+    velocity_windows: list[tuple[float, float, int]] = []
+
+    for row_index in range(1, len(rows)):
+        previous = rows[row_index - 1]
+        current = rows[row_index]
+        dt = current[0] - previous[0]
+        if dt <= 0.0:
+            raise ValueError(f"Non-positive dt at line {row_index + 1}: {dt}")
+
+        velocity_row = []
+        for joint_index in range(joint_count):
+            dq_native = current[joint_index + 1] - previous[joint_index + 1]
+            dq_rad = to_radians(dq_native, unit)
+            velocity_row.append(dq_rad / dt)
+
+        velocities_rad.append(velocity_row)
+        velocity_windows.append((previous[0], current[0], row_index + 1))
+
+    peaks: list[PeakMetric | None] = [None] * joint_count
+
+    for velocity_index in range(1, len(velocities_rad)):
+        dt = velocity_windows[velocity_index][1] - velocity_windows[velocity_index][0]
+        for joint_index in range(joint_count):
+            acceleration_rad = (velocities_rad[velocity_index][joint_index] - velocities_rad[velocity_index - 1][joint_index]) / dt
+            acceleration_native = to_native_from_rad(acceleration_rad, unit)
+
+            candidate = PeakMetric(
+                joint_name=limits[joint_index].name,
+                axis_index=joint_index + 1,
+                window_start=velocity_windows[velocity_index][0],
+                window_end=velocity_windows[velocity_index][1],
+                row_number=velocity_windows[velocity_index][2],
+                metric_native=acceleration_native,
+                metric_rad=acceleration_rad,
+                effective_limit_rad=limits[joint_index].acceleration,
+            )
+
+            current_peak = peaks[joint_index]
+            if current_peak is None or abs(candidate.metric_rad) > abs(current_peak.metric_rad):
+                peaks[joint_index] = candidate
+
+    return [peak for peak in peaks if peak is not None]
+
+
+def calculate_jerk_peaks(rows: list[list[float]], unit: str, limits: list[JointLimit]) -> list[PeakMetric]:
+    joint_count = len(rows[0]) - 1
+    if joint_count != len(limits):
+        raise ValueError(f"Joint column count ({joint_count}) does not match robot limit count ({len(limits)}).")
+
+    velocities_rad: list[list[float]] = []
+    velocity_windows: list[tuple[float, float, int]] = []
+    for row_index in range(1, len(rows)):
+        previous = rows[row_index - 1]
+        current = rows[row_index]
+        dt = current[0] - previous[0]
+        if dt <= 0.0:
+            raise ValueError(f"Non-positive dt at line {row_index + 1}: {dt}")
+
+        velocity_row = []
+        for joint_index in range(joint_count):
+            dq_native = current[joint_index + 1] - previous[joint_index + 1]
+            dq_rad = to_radians(dq_native, unit)
+            velocity_row.append(dq_rad / dt)
+
+        velocities_rad.append(velocity_row)
+        velocity_windows.append((previous[0], current[0], row_index + 1))
+
+    accelerations_rad: list[list[float]] = []
+    acceleration_windows: list[tuple[float, float, int]] = []
+    for velocity_index in range(1, len(velocities_rad)):
+        dt = velocity_windows[velocity_index][1] - velocity_windows[velocity_index][0]
+        acceleration_row = []
+        for joint_index in range(joint_count):
+            acceleration_row.append((velocities_rad[velocity_index][joint_index] - velocities_rad[velocity_index - 1][joint_index]) / dt)
+        accelerations_rad.append(acceleration_row)
+        acceleration_windows.append((velocity_windows[velocity_index][0], velocity_windows[velocity_index][1], velocity_windows[velocity_index][2]))
+
+    peaks: list[PeakMetric | None] = [None] * joint_count
+
+    for acceleration_index in range(1, len(accelerations_rad)):
+        dt = acceleration_windows[acceleration_index][1] - acceleration_windows[acceleration_index][0]
+        for joint_index in range(joint_count):
+            jerk_rad = (accelerations_rad[acceleration_index][joint_index] - accelerations_rad[acceleration_index - 1][joint_index]) / dt
+            jerk_native = to_native_from_rad(jerk_rad, unit)
+
+            candidate = PeakMetric(
+                joint_name=limits[joint_index].name,
+                axis_index=joint_index + 1,
+                window_start=acceleration_windows[acceleration_index][0],
+                window_end=acceleration_windows[acceleration_index][1],
+                row_number=acceleration_windows[acceleration_index][2],
+                metric_native=jerk_native,
+                metric_rad=jerk_rad,
+                effective_limit_rad=limits[joint_index].jerk,
+            )
+
+            current_peak = peaks[joint_index]
+            if current_peak is None or abs(candidate.metric_rad) > abs(current_peak.metric_rad):
+                peaks[joint_index] = candidate
+
+    return [peak for peak in peaks if peak is not None]
+
+
+def format_table(peaks: list[PeakMetric], native_unit: str, rad_unit: str, limit_header: str) -> str:
+    lines = [
+        f"{'Joint':<8} {'Window(s)':<20} {'Line':>6} {'Peak(' + native_unit + ')':>18} {'Peak(' + rad_unit + ')':>18} {limit_header:>20} {'Ratio':>10}",
+        "-" * 108,
+    ]
+    for peak in peaks:
+        lines.append(
+            f"{peak.joint_name:<8} "
+            f"{peak.window_start:>7.6f}->{peak.window_end:<10.6f} "
+            f"{peak.row_number:>6} "
+            f"{peak.metric_native:>18.6f} "
+            f"{peak.metric_rad:>18.6f} "
+            f"{peak.effective_limit_rad:>20.6f} "
+            f"{peak.ratio_vs_limit:>10.4f}"
+        )
+    return "\n".join(lines)
+
+
+def print_metric_section(title: str, peaks: list[PeakMetric], unit: str, native_suffix: str, rad_suffix: str, limit_header: str) -> None:
+    print(build_metric_section(title, peaks, unit, native_suffix, rad_suffix, limit_header))
+
+
+def build_metric_section(title: str, peaks: list[PeakMetric], unit: str, native_suffix: str, rad_suffix: str, limit_header: str) -> str:
+    native_unit = f"deg/{native_suffix}" if unit == "deg" else f"rad/{native_suffix}"
+    rad_unit = f"rad/{rad_suffix}"
+    lines = [title, format_table(peaks, native_unit, rad_unit, limit_header)]
+    worst = max(peaks, key=lambda item: item.ratio_vs_limit)
+    metric_key = title.lower().replace(" ", "_")
+    lines.append(
+        f"worst_{metric_key}="
+        f"{worst.joint_name}, window={worst.window_start:.6f}->{worst.window_end:.6f}, "
+        f"peak_rad={worst.metric_rad:.6f}, limit_rad={worst.effective_limit_rad:.6f}, "
+        f"ratio={worst.ratio_vs_limit:.4f}"
+    )
+    return "\n".join(lines)
+
+
+def build_report_text(
+    joint_detail_path: Path,
+    rows: list[list[float]],
+    unit: str,
+    max_abs_joint: float,
+    limit_source_text: str,
+    trim_note: str | None,
+    velocity_peaks: list[PeakMetric],
+    acceleration_peaks: list[PeakMetric],
+    jerk_peaks: list[PeakMetric],
+) -> str:
+    lines = [
+        f"joint_detail={joint_detail_path}",
+        limit_source_text,
+        f"row_count={len(rows)}",
+        f"joint_count={len(rows[0]) - 1}",
+        f"inferred_unit={unit}",
+        f"max_abs_joint_value={max_abs_joint:.6f}",
+    ]
+    if trim_note is not None:
+        lines.append(trim_note)
+    lines.extend(
+        [
+            "",
+            build_metric_section("Velocity Peaks", velocity_peaks, unit, "s", "s", "VelLimit(rad/s)"),
+            "",
+            build_metric_section("Acceleration Peaks", acceleration_peaks, unit, "s^2", "s^2", "AccLimit(rad/s^2)"),
+            "",
+            build_metric_section("Jerk Peaks", jerk_peaks, unit, "s^3", "s^3", "JerkLimit(rad/s^3)"),
+            "",
+        ]
+    )
+    return "\n".join(lines)
+
+
+def main() -> int:
+    args = parse_args()
+    joint_detail_path = resolve_path(args.joint_detail)
+    rows = read_joint_rows(joint_detail_path)
+    limits_info = load_effective_limits(args.limit_csv)
+    rows, trim_note = trim_rows_to_limit_count(rows, len(limits_info.joints))
+    unit = infer_unit(rows, args.unit)
+
+    velocity_peaks = calculate_velocity_peaks(rows, unit, limits_info.joints)
+    acceleration_peaks = calculate_acceleration_peaks(rows, unit, limits_info.joints)
+    jerk_peaks = calculate_jerk_peaks(rows, unit, limits_info.joints)
+
+    max_abs_joint = max(abs(value) for row in rows for value in row[1:])
+
+    if args.limit_csv is None:
+        limit_source_text = "limit_source=built-in fixed effective limits (acc_limit=1, jerk_limit=1)"
+    else:
+        limit_source_text = f"limit_source_csv={resolve_path(args.limit_csv)}"
+
+    report_text = build_report_text(
+        joint_detail_path=joint_detail_path,
+        rows=rows,
+        unit=unit,
+        max_abs_joint=max_abs_joint,
+        limit_source_text=limit_source_text,
+        trim_note=trim_note,
+        velocity_peaks=velocity_peaks,
+        acceleration_peaks=acceleration_peaks,
+        jerk_peaks=jerk_peaks,
+    )
+
+    print(report_text, end="")
+
+    output_path = joint_detail_path.with_suffix(".analysis.txt")
+    try:
+        output_path.write_text(report_text, encoding="utf-8")
+        print(f"saved_report={output_path}")
+    except PermissionError as error:
+        print(f"save_report_failed={output_path}")
+        print(f"save_report_error={error}")
+
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

analysis/fanuc_10010_dissector.lua

@@ -0,0 +1,199 @@
+local plugin_info = {
+    version = "1.1.0",
+    author = "OpenAI Codex",
+    description = "FANUC TCP 10010 状态帧解析器",
+}
+
+set_plugin_info(plugin_info)
+
+local fanuc10010_proto = Proto("fanuc10010_state_frame", "FANUC 10010 State Frame")
+
+local FRAME_LENGTH = 90
+local HEADER_LENGTH = 3
+local TRAILER_LENGTH = 3
+local LENGTH_OFFSET = 3
+local MESSAGE_ID_OFFSET = 7
+local POSE_OFFSET = 11
+local POSE_COUNT = 6
+local JOINT_OFFSET = 35
+local JOINT_COUNT = 9
+local TAIL_OFFSET = 71
+local TAIL_COUNT = 4
+
+local POSE_NAMES = { "X", "Y", "Z", "W", "P", "R" }
+local JOINT_NAMES = { "J1", "J2", "J3", "J4", "J5", "J6", "Ext1", "Ext2", "Ext3" }
+local HEADER_MAGIC = "doz"
+local TRAILER_MAGIC = "zod"
+
+local fields = {
+    frame = ProtoField.bytes("fanuc10010.frame", "原始状态帧"),
+    header = ProtoField.string("fanuc10010.header", "帧头 Magic"),
+    declared_length = ProtoField.uint32("fanuc10010.length", "声明长度", base.DEC),
+    message_id = ProtoField.uint32("fanuc10010.message_id", "消息号", base.DEC),
+    pose = ProtoField.none("fanuc10010.pose", "笛卡尔位姿"),
+    joints = ProtoField.none("fanuc10010.joints", "关节与扩展轴"),
+    joint_degrees = ProtoField.none("fanuc10010.joint_degrees", "Joint Degrees"),
+    tail = ProtoField.none("fanuc10010.tail", "尾部状态字"),
+    trailer = ProtoField.string("fanuc10010.trailer", "帧尾 Magic"),
+    expert_bad_length = ProtoField.string("fanuc10010.expert.bad_length", "长度异常"),
+    expert_bad_magic = ProtoField.string("fanuc10010.expert.bad_magic", "Magic 异常"),
+}
+
+for index = 1, POSE_COUNT do
+    fields["pose_" .. index] = ProtoField.float(
+        "fanuc10010.pose_" .. index,
+        "Pose " .. POSE_NAMES[index])
+end
+
+for index = 1, JOINT_COUNT do
+    fields["joint_" .. index] = ProtoField.float(
+        "fanuc10010.joint_" .. index,
+        JOINT_NAMES[index] .. " (raw)")
+end
+
+for index = 1, 6 do
+    fields["joint_deg_" .. index] = ProtoField.float(
+        "fanuc10010.joint_deg_" .. index,
+        JOINT_NAMES[index] .. " (deg)")
+end
+
+for index = 1, TAIL_COUNT do
+    fields["tail_" .. index] = ProtoField.uint32(
+        "fanuc10010.tail_" .. index,
+        "Tail[" .. (index - 1) .. "]",
+        base.DEC)
+end
+
+fanuc10010_proto.fields = fields
+
+local function read_f32_be(tvb, offset)
+    return tvb(offset, 4):tvb():range(0, 4):float()
+end
+
+local function read_u32_be(tvb, offset)
+    return tvb(offset, 4):uint()
+end
+
+local function read_ascii(tvb, offset, length)
+    return tvb(offset, length):string()
+end
+
+local function radians_to_degrees(value)
+    return value * 180.0 / math.pi
+end
+
+local function add_error(subtree, range, field, message)
+    local item = subtree:add(field, range, message)
+    item:add_expert_info(PI_MALFORMED, PI_ERROR, message)
+end
+
+local function dissect_single_frame(tvb, pinfo, tree, frame_offset)
+    local remaining = tvb:len() - frame_offset
+    local candidate_length = math.min(remaining, FRAME_LENGTH)
+    local frame_range = tvb(frame_offset, candidate_length)
+    local subtree = tree:add(fanuc10010_proto, frame_range, "FANUC 10010 状态帧")
+    subtree:add(fields.frame, frame_range)
+
+    if remaining < FRAME_LENGTH then
+        add_error(subtree, frame_range, fields.expert_bad_length, "剩余字节不足 90B，无法组成完整状态帧")
+        return remaining
+    end
+
+    local header = read_ascii(tvb, frame_offset, HEADER_LENGTH)
+    local declared_length = read_u32_be(tvb, frame_offset + LENGTH_OFFSET)
+    local message_id = read_u32_be(tvb, frame_offset + MESSAGE_ID_OFFSET)
+    local trailer = read_ascii(tvb, frame_offset + FRAME_LENGTH - TRAILER_LENGTH, TRAILER_LENGTH)
+
+    subtree:add(fields.header, tvb(frame_offset, HEADER_LENGTH), header)
+    subtree:add(fields.declared_length, tvb(frame_offset + LENGTH_OFFSET, 4), declared_length)
+    subtree:add(fields.message_id, tvb(frame_offset + MESSAGE_ID_OFFSET, 4), message_id)
+
+    local pose_tree = subtree:add(fields.pose, tvb(frame_offset + POSE_OFFSET, POSE_COUNT * 4))
+    local pose_values = {}
+    for index = 1, POSE_COUNT do
+        local field_offset = frame_offset + POSE_OFFSET + ((index - 1) * 4)
+        local value = read_f32_be(tvb, field_offset)
+        pose_values[index] = value
+        pose_tree:add(fields["pose_" .. index], tvb(field_offset, 4), value)
+    end
+
+    local joint_tree = subtree:add(fields.joints, tvb(frame_offset + JOINT_OFFSET, JOINT_COUNT * 4))
+    local joint_values = {}
+    for index = 1, JOINT_COUNT do
+        local field_offset = frame_offset + JOINT_OFFSET + ((index - 1) * 4)
+        local value = read_f32_be(tvb, field_offset)
+        joint_values[index] = value
+        joint_tree:add(fields["joint_" .. index], tvb(field_offset, 4), value)
+    end
+
+    -- 单独保留一组角度显示，便于对照原始关节弧度值。
+    local joint_degree_tree = subtree:add(fields.joint_degrees, tvb(frame_offset + JOINT_OFFSET, 6 * 4))
+    for index = 1, 6 do
+        local field_offset = frame_offset + JOINT_OFFSET + ((index - 1) * 4)
+        joint_degree_tree:add(
+            fields["joint_deg_" .. index],
+            tvb(field_offset, 4),
+            radians_to_degrees(joint_values[index]))
+    end
+
+    local tail_tree = subtree:add(fields.tail, tvb(frame_offset + TAIL_OFFSET, TAIL_COUNT * 4))
+    local tail_values = {}
+    for index = 1, TAIL_COUNT do
+        local field_offset = frame_offset + TAIL_OFFSET + ((index - 1) * 4)
+        local value = read_u32_be(tvb, field_offset)
+        tail_values[index] = value
+        tail_tree:add(fields["tail_" .. index], tvb(field_offset, 4), value)
+    end
+
+    subtree:add(fields.trailer, tvb(frame_offset + FRAME_LENGTH - TRAILER_LENGTH, TRAILER_LENGTH), trailer)
+
+    if header ~= HEADER_MAGIC then
+        add_error(subtree, tvb(frame_offset, HEADER_LENGTH), fields.expert_bad_magic, "帧头不是 doz")
+    end
+
+    if trailer ~= TRAILER_MAGIC then
+        add_error(subtree, tvb(frame_offset + FRAME_LENGTH - TRAILER_LENGTH, TRAILER_LENGTH), fields.expert_bad_magic, "帧尾不是 zod")
+    end
+
+    if declared_length ~= FRAME_LENGTH then
+        add_error(subtree, tvb(frame_offset + LENGTH_OFFSET, 4), fields.expert_bad_length, "长度字段不是 90")
+    end
+
+    local summary = string.format(
+        "MsgId=%u X=%.3f Y=%.3f Z=%.3f J1=%.6f rad / %.3f deg J2=%.6f rad / %.3f deg Tail=[%u,%u,%u,%u]",
+        message_id,
+        pose_values[1], pose_values[2], pose_values[3],
+        joint_values[1], radians_to_degrees(joint_values[1]),
+        joint_values[2], radians_to_degrees(joint_values[2]),
+        tail_values[1], tail_values[2], tail_values[3], tail_values[4])
+
+    subtree:set_text("FANUC 10010 状态帧, " .. summary)
+    pinfo.cols.info:append(" | " .. summary)
+
+    return FRAME_LENGTH
+end
+
+function fanuc10010_proto.dissector(tvb, pinfo, tree)
+    if tvb:len() == 0 then
+        return 0
+    end
+
+    pinfo.cols.protocol = "FANUC10010"
+
+    local offset = 0
+    while offset < tvb:len() do
+        local consumed = dissect_single_frame(tvb, pinfo, tree, offset)
+        if consumed <= 0 then
+            break
+        end
+
+        offset = offset + consumed
+        if consumed < FRAME_LENGTH then
+            break
+        end
+    end
+
+    return tvb:len()
+end
+
+DissectorTable.get("tcp.port"):add(10010, fanuc10010_proto)

analysis/read_fanuc_allowable_limits.py

@@ -0,0 +1,200 @@
+#!/usr/bin/env python3
+"""读取 FANUC J519 允许速度/加速度/jerk 上限表。
+
+本脚本只做 UDP packet type=3 查询，不启动运行时服务，也不写入机器人参数。
+响应中的 limit 值保留为控制器原始单位：速度 deg/s、加速度 deg/s^2、jerk deg/s^3。
+"""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import socket
+import struct
+import sys
+from dataclasses import dataclass
+from pathlib import Path
+
+
+LIMIT_TYPES = {
+    0: ("velocity", "deg/s"),
+    1: ("acceleration", "deg/s^2"),
+    2: ("jerk", "deg/s^3"),
+}
+
+
+@dataclass(frozen=True)
+class LimitTable:
+    """保存单个轴、单种限制类型的 20 档 no-payload / max-payload 上限表。"""
+
+    axis: int
+    limit_type: int
+    vmax_mm_s: int
+    intermediate_check_s: int
+    no_payload: tuple[float, ...]
+    max_payload: tuple[float, ...]
+
+
+def pack_request(axis: int, limit_type: int) -> bytes:
+    """按手册 Table 5 封装允许上限表查询请求。"""
+
+    return struct.pack(">IIII", 3, 1, axis, limit_type)
+
+
+def parse_response(packet: bytes, expected_axis: int, expected_type: int) -> LimitTable:
+    """按手册 Table 6 解析允许上限表响应。"""
+
+    if len(packet) != 184:
+        raise ValueError(f"响应长度应为 184 字节，实际为 {len(packet)} 字节。")
+
+    packet_type, version, axis, limit_type, vmax, check_time = struct.unpack_from(">IIIIII", packet, 0)
+    if packet_type != 3 or version != 1:
+        raise ValueError(f"响应头不正确：packet_type={packet_type}, version={version}。")
+    if axis != expected_axis or limit_type != expected_type:
+        raise ValueError(
+            f"响应与请求不匹配：期望 axis={expected_axis}, type={expected_type}，"
+            f"实际 axis={axis}, type={limit_type}。"
+        )
+
+    values = struct.unpack_from(">40f", packet, 24)
+    return LimitTable(
+        axis=axis,
+        limit_type=limit_type,
+        vmax_mm_s=vmax,
+        intermediate_check_s=check_time,
+        no_payload=tuple(values[:20]),
+        max_payload=tuple(values[20:]),
+    )
+
+
+def query_table(sock: socket.socket, robot_ip: str, port: int, axis: int, limit_type: int) -> LimitTable:
+    """发送单个查询请求并等待对应响应。"""
+
+    sock.sendto(pack_request(axis, limit_type), (robot_ip, port))
+    packet, address = sock.recvfrom(2048)
+    if address[0] != robot_ip:
+        raise ValueError(f"收到非目标机器人响应：{address[0]}:{address[1]}。")
+    return parse_response(packet, axis, limit_type)
+
+
+def iter_requested_tables(
+    robot_ip: str,
+    port: int,
+    timeout_s: float,
+    axes: range,
+    limit_types: tuple[int, ...],
+) -> list[LimitTable]:
+    """按轴和限制类型顺序读取所有上限表。"""
+
+    tables: list[LimitTable] = []
+    with socket.socket(socket.AF_INET, socket.SOCK_DGRAM) as sock:
+        sock.settimeout(timeout_s)
+        for axis in axes:
+            for limit_type in limit_types:
+                tables.append(query_table(sock, robot_ip, port, axis, limit_type))
+    return tables
+
+
+def write_csv(path: Path, tables: list[LimitTable]) -> None:
+    """把 20 档速度区间和两套 payload 表写成扁平 CSV。"""
+
+    with path.open("w", newline="", encoding="utf-8") as file:
+        writer = csv.writer(file)
+        writer.writerow(
+            [
+                "axis",
+                "limit_type",
+                "unit",
+                "vmax_mm_s",
+                "intermediate_check_s",
+                "speed_bin_index",
+                "speed_bin_upper_mm_s",
+                "no_payload_limit",
+                "max_payload_limit",
+            ]
+        )
+        for table in tables:
+            limit_name, unit = LIMIT_TYPES[table.limit_type]
+            for index, (no_payload, max_payload) in enumerate(zip(table.no_payload, table.max_payload), start=1):
+                writer.writerow(
+                    [
+                        table.axis,
+                        limit_name,
+                        unit,
+                        table.vmax_mm_s,
+                        table.intermediate_check_s,
+                        index,
+                        table.vmax_mm_s * index / 20.0,
+                        f"{no_payload:.9g}",
+                        f"{max_payload:.9g}",
+                    ]
+                )
+
+
+def print_summary(tables: list[LimitTable]) -> None:
+    """打印每张表的首末档，便于现场快速确认返回值是否正常。"""
+
+    for table in tables:
+        limit_name, unit = LIMIT_TYPES[table.limit_type]
+        print(
+            f"axis={table.axis} type={limit_name:<12} unit={unit:<8} "
+            f"vmax={table.vmax_mm_s}mm/s check={table.intermediate_check_s}s "
+            f"no_payload[1]={table.no_payload[0]:.6g} no_payload[20]={table.no_payload[-1]:.6g} "
+            f"max_payload[1]={table.max_payload[0]:.6g} max_payload[20]={table.max_payload[-1]:.6g}"
+        )
+
+
+def parse_args() -> argparse.Namespace:
+    """解析命令行参数。"""
+
+    parser = argparse.ArgumentParser(
+        description="Read FANUC J519 packet type=3 allowable upper limit tables.",
+    )
+    parser.add_argument("robot_ip", help="机器人控制柜 IP，例如 192.168.10.11。")
+    parser.add_argument("--port", type=int, default=60015, help="J519 UDP 端口，默认 60015。")
+    parser.add_argument("--timeout", type=float, default=2.0, help="单次响应超时秒数，默认 2.0。")
+    parser.add_argument("--axis-start", type=int, default=1, help="起始轴号，默认 1。")
+    parser.add_argument("--axis-end", type=int, default=9, help="结束轴号，默认 9。")
+    parser.add_argument(
+        "--types",
+        default="0,1,2",
+        help="限制类型列表：0=velocity, 1=acceleration, 2=jerk；默认 0,1,2。",
+    )
+    parser.add_argument(
+        "--csv",
+        type=Path,
+        default=Path("analysis/fanuc_allowable_limit_tables.csv"),
+        help="CSV 输出路径。",
+    )
+    return parser.parse_args()
+
+
+def main() -> int:
+    """脚本入口。"""
+
+    args = parse_args()
+    limit_types = tuple(int(item.strip()) for item in args.types.split(",") if item.strip())
+    unknown_types = [item for item in limit_types if item not in LIMIT_TYPES]
+    if unknown_types:
+        print(f"未知限制类型：{unknown_types}", file=sys.stderr)
+        return 2
+    if not 1 <= args.axis_start <= args.axis_end <= 9:
+        print("轴范围必须满足 1 <= axis-start <= axis-end <= 9。", file=sys.stderr)
+        return 2
+
+    tables = iter_requested_tables(
+        args.robot_ip,
+        args.port,
+        args.timeout,
+        range(args.axis_start, args.axis_end + 1),
+        limit_types,
+    )
+    args.csv.parent.mkdir(parents=True, exist_ok=True)
+    write_csv(args.csv, tables)
+    print_summary(tables)
+    print(f"\nCSV 已写入：{args.csv}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

analysis/segment_02_acc_jerk_summary.csv

@@ -0,0 +1,7 @@
+Axis,AccPeakRadPerS2,AccLimitRadPerS2,AccRatio,AccWindowStartS,AccWindowEndS,AccLine,JerkPeakRadPerS3,JerkLimitRadPerS3,JerkRatio,JerkWindowStartS,JerkWindowEndS,JerkLine
+Joint1,16.638678,26.900000,0.618538,0.128012,0.135939,18,902.687973,224.220000,4.025903,6.312082,6.320127,791
+Joint2,14.521836,22.540000,0.644270,3.088013,3.096086,388,888.335197,187.860000,4.728709,2.904052,2.912069,365
+Joint3,14.267221,29.810000,0.478605,0.128012,0.135939,18,728.505873,248.460000,2.932085,0.135939,0.143989,19
+Joint4,-34.694506,39.990000,0.867580,6.832125,6.840105,856,-2222.596524,333.300000,6.668456,6.312082,6.320127,791
+Joint5,-16.329775,39.630000,0.412056,6.840105,6.848111,857,842.738923,330.270000,2.551667,6.936077,6.944096,869
+Joint6,34.766065,72.720000,0.478081,1.392021,1.399995,176,2678.050822,606.010000,4.419153,6.312082,6.320127,791