#!/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()