yunxiao.zhu
70b0ccd414
- 改为高优先级 J519 接收线程与复用缓冲区发送链路 - 增加稠密执行前的 J519 就绪重试与状态诊断 - 修正程序状态响应字段顺序与 EnableRobot 默认参数 - 为飞拍轨迹补充平滑起停时间轴与首尾整形验证 - 补充真实运行配置、报警窗口与边界对比测试 - 同步更新限值文档、分析脚本与 .NET 8 SDK 固定配置
479 lines
19 KiB
C#
479 lines
19 KiB
C#
using Flyshot.Core.Config;
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using Flyshot.Core.Domain;
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using Flyshot.Core.Planning;
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using Flyshot.Core.Planning.Sampling;
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using Flyshot.Core.Triggering;
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using Microsoft.Extensions.Logging;
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namespace Flyshot.ControllerClientCompat;
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/// <summary>
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/// 负责把 ControllerClient 兼容层的轨迹输入转换为规划结果和触发时间轴。
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/// </summary>
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public sealed class ControllerClientTrajectoryOrchestrator
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{
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private readonly ICspPlanner _icspPlanner;
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private readonly SelfAdaptIcspPlanner _selfAdaptIcspPlanner;
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private readonly ShotTimelineBuilder _shotTimelineBuilder = new(new WaypointTimestampResolver());
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private readonly Dictionary<string, PlannedExecutionBundle> _flyshotCache = new(StringComparer.Ordinal);
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private readonly ILogger<ControllerClientTrajectoryOrchestrator>? _logger;
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/// <summary>
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/// 初始化轨迹编排器。
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/// </summary>
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/// <param name="logger">日志记录器；允许 null。</param>
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public ControllerClientTrajectoryOrchestrator(ILogger<ControllerClientTrajectoryOrchestrator>? logger = null)
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{
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_logger = logger;
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_icspPlanner = new(logger: null);
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_selfAdaptIcspPlanner = new(logger: null);
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}
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/// <summary>
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/// 对普通轨迹执行 ICSP 规划。
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/// </summary>
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/// <param name="robot">当前机器人配置。</param>
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/// <param name="waypoints">普通轨迹关节路点。</param>
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/// <returns>包含规划轨迹、空触发时间轴和执行结果的结果包。</returns>
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public PlannedExecutionBundle PlanOrdinaryTrajectory(
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RobotProfile robot,
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IReadOnlyList<IReadOnlyList<double>> waypoints,
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TrajectoryExecutionOptions? options = null,
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double planningSpeedScale = 1.0)
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{
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ArgumentNullException.ThrowIfNull(robot);
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ArgumentNullException.ThrowIfNull(waypoints);
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options ??= new TrajectoryExecutionOptions();
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var planningRobot = ApplyPlanningSpeedScale(robot, planningSpeedScale);
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_logger?.LogInformation(
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"PlanOrdinaryTrajectory 开始: 路点数={WaypointCount}, method={Method}, planningSpeedScale={PlanningSpeedScale}",
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waypoints.Count, options.Method, planningSpeedScale);
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var program = CreateProgram(
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name: "ordinary-trajectory",
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waypoints: waypoints,
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shotFlags: Enumerable.Repeat(false, waypoints.Count),
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offsetValues: Enumerable.Repeat(0, waypoints.Count),
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addressGroups: Enumerable.Range(0, waypoints.Count).Select(static _ => Array.Empty<int>()));
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var method = ParseOrdinaryMethod(options.Method);
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var request = new TrajectoryRequest(
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robot: planningRobot,
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program: program,
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method: method,
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saveTrajectoryArtifacts: options.SaveTrajectory);
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var plannedTrajectory = PlanByMethod(request, method);
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var shotTimeline = new ShotTimeline(Array.Empty<ShotEvent>(), Array.Empty<TrajectoryDoEvent>());
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var result = CreateResult(plannedTrajectory, shotTimeline, usedCache: false, shapeTrajectoryEdges: false);
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_logger?.LogInformation(
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"PlanOrdinaryTrajectory 完成: 时长={Duration}s, 采样点数={SampleCount}",
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result.Duration.TotalSeconds,
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result.DenseJointTrajectory?.Count ?? 0);
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return new PlannedExecutionBundle(plannedTrajectory, shotTimeline, result);
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}
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/// <summary>
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/// 对已经上传的飞拍轨迹执行自适应 ICSP 规划并生成触发时间轴。
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/// </summary>
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/// <param name="robot">当前机器人配置。</param>
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/// <param name="uploaded">兼容层保存的上传轨迹。</param>
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/// <returns>包含规划轨迹、触发时间轴和执行结果的结果包。</returns>
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public PlannedExecutionBundle PlanUploadedFlyshot(
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RobotProfile robot,
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ControllerClientCompatUploadedTrajectory uploaded,
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FlyshotExecutionOptions? options = null,
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CompatibilityRobotSettings? settings = null,
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double? planningSpeedScale = null)
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{
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ArgumentNullException.ThrowIfNull(robot);
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ArgumentNullException.ThrowIfNull(uploaded);
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options ??= new FlyshotExecutionOptions();
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settings ??= CreateDefaultRobotSettings();
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var effectivePlanningSpeedScale = planningSpeedScale ?? settings.PlanningSpeedScale;
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var planningRobot = ApplyPlanningSpeedScale(robot, effectivePlanningSpeedScale);
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_logger?.LogInformation(
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"PlanUploadedFlyshot 开始: name={Name}, waypoints={WaypointCount}, method={Method}, useCache={UseCache}, planningSpeedScale={PlanningSpeedScale}",
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uploaded.Name, uploaded.Waypoints.Count, options.Method, options.UseCache, effectivePlanningSpeedScale);
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var program = CreateProgram(
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name: uploaded.Name,
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waypoints: uploaded.Waypoints,
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shotFlags: uploaded.ShotFlags,
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offsetValues: uploaded.OffsetValues,
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addressGroups: uploaded.AddressGroups);
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var method = ParseFlyshotMethod(options.Method);
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var cacheKey = CreateFlyshotCacheKey(planningRobot, uploaded, options, settings, effectivePlanningSpeedScale);
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if (options.UseCache && _flyshotCache.TryGetValue(cacheKey, out var cachedBundle))
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{
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_logger?.LogInformation("PlanUploadedFlyshot 命中缓存: name={Name}, cacheKey={CacheKey}", uploaded.Name, cacheKey);
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var executionTrajectory = ApplySmoothStartStopTiming(cachedBundle.PlannedTrajectory);
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var executionTimeline = _shotTimelineBuilder.Build(
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executionTrajectory,
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holdCycles: settings.IoKeepCycles,
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samplePeriod: planningRobot.ServoPeriod,
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useDo: settings.UseDo);
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// 命中缓存时只替换 TrajectoryResult 的 usedCache 标志，规划轨迹和触发时间轴保持不可变复用。
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return new PlannedExecutionBundle(
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cachedBundle.PlannedTrajectory,
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executionTimeline,
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CreateResult(executionTrajectory, executionTimeline, usedCache: true, shapeTrajectoryEdges: false));
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}
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var request = new TrajectoryRequest(
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robot: planningRobot,
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program: program,
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method: method,
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moveToStart: options.MoveToStart,
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saveTrajectoryArtifacts: options.SaveTrajectory,
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useCache: options.UseCache);
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var plannedTrajectory = PlanByMethod(request, method, settings);
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var smoothedExecutionTrajectory = ApplySmoothStartStopTiming(plannedTrajectory);
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var shotTimeline = _shotTimelineBuilder.Build(
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smoothedExecutionTrajectory,
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holdCycles: settings.IoKeepCycles,
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samplePeriod: planningRobot.ServoPeriod,
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useDo: settings.UseDo);
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var result = CreateResult(smoothedExecutionTrajectory, shotTimeline, usedCache: false, shapeTrajectoryEdges: false);
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var bundle = new PlannedExecutionBundle(plannedTrajectory, shotTimeline, result);
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_logger?.LogInformation(
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"PlanUploadedFlyshot 完成: name={Name}, 时长={Duration}s, 触发事件数={TriggerCount}, 采样点数={SampleCount}",
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uploaded.Name, result.Duration.TotalSeconds, result.TriggerTimeline.Count, result.DenseJointTrajectory?.Count ?? 0);
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if (options.UseCache)
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{
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_flyshotCache[cacheKey] = bundle;
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}
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return bundle;
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}
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/// <summary>
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/// 按普通轨迹执行接口约束解析 method 参数。
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/// </summary>
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/// <param name="method">旧 SDK 传入的方法名。</param>
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/// <returns>领域层规划方法。</returns>
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private static PlanningMethod ParseOrdinaryMethod(string method)
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{
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var normalized = NormalizeMethod(method);
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return normalized switch
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{
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"icsp" => PlanningMethod.Icsp,
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"doubles" => PlanningMethod.Doubles,
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_ => throw new ArgumentException($"Unsupported ExecuteTrajectory method: {method}", nameof(method))
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};
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}
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/// <summary>
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/// 按飞拍轨迹执行接口约束解析 method 参数。
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/// </summary>
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/// <param name="method">旧 SDK 传入的方法名。</param>
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/// <returns>领域层规划方法。</returns>
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private static PlanningMethod ParseFlyshotMethod(string method)
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{
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var normalized = NormalizeMethod(method);
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return normalized switch
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{
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"icsp" => PlanningMethod.Icsp,
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"self-adapt-icsp" => PlanningMethod.SelfAdaptIcsp,
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"doubles" => PlanningMethod.Doubles,
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_ => throw new ArgumentException($"Unsupported ExecuteFlyShotTraj method: {method}", nameof(method))
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};
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}
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/// <summary>
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/// 按领域枚举分派到当前已经落地的规划器。
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/// </summary>
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/// <param name="request">规划请求。</param>
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/// <param name="method">规划方法。</param>
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/// <returns>规划轨迹。</returns>
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private PlannedTrajectory PlanByMethod(TrajectoryRequest request, PlanningMethod method, CompatibilityRobotSettings? settings = null)
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{
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return method switch
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{
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PlanningMethod.Icsp => _icspPlanner.Plan(request),
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PlanningMethod.SelfAdaptIcsp => _selfAdaptIcspPlanner.Plan(request, settings?.AdaptIcspTryNum ?? 5),
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PlanningMethod.Doubles => throw new NotSupportedException("doubles 轨迹规划尚未落地。"),
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_ => throw new ArgumentOutOfRangeException(nameof(method), method, "未知轨迹规划方法。")
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};
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}
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/// <summary>
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/// 归一化旧 SDK 的 method 字符串。
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/// </summary>
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/// <param name="method">原始方法名。</param>
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/// <returns>小写短横线方法名。</returns>
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private static string NormalizeMethod(string method)
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{
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if (string.IsNullOrWhiteSpace(method))
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{
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return "icsp";
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}
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return method.Trim().ToLowerInvariant();
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}
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/// <summary>
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/// 为已上传飞拍轨迹构造包含参数和轨迹内容的缓存键，避免同名覆盖后误用旧规划结果。
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/// </summary>
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/// <param name="robot">机器人配置。</param>
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/// <param name="uploaded">上传轨迹。</param>
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/// <param name="options">执行参数。</param>
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/// <returns>缓存键。</returns>
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private static string CreateFlyshotCacheKey(
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RobotProfile robot,
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ControllerClientCompatUploadedTrajectory uploaded,
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FlyshotExecutionOptions options,
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CompatibilityRobotSettings settings,
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double planningSpeedScale)
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{
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var hash = new HashCode();
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hash.Add(robot.Name, StringComparer.Ordinal);
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hash.Add(planningSpeedScale);
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hash.Add(uploaded.Name, StringComparer.Ordinal);
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hash.Add(NormalizeMethod(options.Method), StringComparer.Ordinal);
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hash.Add(options.MoveToStart);
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hash.Add(options.SaveTrajectory);
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hash.Add(settings.UseDo);
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hash.Add(settings.IoKeepCycles);
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hash.Add(settings.AdaptIcspTryNum);
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foreach (var limit in robot.JointLimits)
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{
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hash.Add(limit.JointName, StringComparer.Ordinal);
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hash.Add(limit.VelocityLimit);
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hash.Add(limit.AccelerationLimit);
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hash.Add(limit.JerkLimit);
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}
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foreach (var waypoint in uploaded.Waypoints)
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{
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foreach (var value in waypoint)
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{
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hash.Add(value);
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}
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}
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foreach (var flag in uploaded.ShotFlags)
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{
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hash.Add(flag);
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}
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foreach (var offset in uploaded.OffsetValues)
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{
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hash.Add(offset);
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}
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foreach (var group in uploaded.AddressGroups)
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{
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foreach (var address in group)
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{
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hash.Add(address);
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}
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}
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return hash.ToHashCode().ToString("X8");
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}
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/// <summary>
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/// 构造编排器直接调用时的默认兼容配置，保持既有单元测试中的 DO 生成行为。
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/// </summary>
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/// <returns>默认机器人兼容配置。</returns>
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private static CompatibilityRobotSettings CreateDefaultRobotSettings()
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{
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return new CompatibilityRobotSettings(
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useDo: true,
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ioAddresses: Array.Empty<int>(),
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ioKeepCycles: 0,
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accLimitScale: 1.0,
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jerkLimitScale: 1.0,
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adaptIcspTryNum: 5);
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}
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/// <summary>
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/// 按规划全局速度倍率生成规划专用机器人约束。
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/// </summary>
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/// <param name="robot">原始机器人约束。</param>
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/// <param name="planningSpeedScale">规划阶段的全局速度倍率，1.0 表示不额外缩放。</param>
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/// <returns>已按速度倍率缩放后的规划机器人约束。</returns>
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private static RobotProfile ApplyPlanningSpeedScale(RobotProfile robot, double planningSpeedScale)
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{
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if (double.IsNaN(planningSpeedScale) || double.IsInfinity(planningSpeedScale) || planningSpeedScale <= 0.0)
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{
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throw new ArgumentOutOfRangeException(nameof(planningSpeedScale), "规划速度倍率必须是有限正数。");
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}
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if (Math.Abs(planningSpeedScale - 1.0) < 1e-12)
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{
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return robot;
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}
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// RVBUST 规划阶段会用独立限速倍率缩放有效限制；运行时 speedRatio 仍只负责 J519 下发重采样。
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var scaledLimits = robot.JointLimits
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.Select(limit => new JointLimit(
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limit.JointName,
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limit.VelocityLimit * planningSpeedScale,
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limit.AccelerationLimit * planningSpeedScale * planningSpeedScale,
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limit.JerkLimit * planningSpeedScale * planningSpeedScale * planningSpeedScale))
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.ToArray();
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return new RobotProfile(
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name: robot.Name,
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modelPath: robot.ModelPath,
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degreesOfFreedom: robot.DegreesOfFreedom,
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jointLimits: scaledLimits,
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jointCouplings: robot.JointCouplings,
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servoPeriod: robot.ServoPeriod,
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triggerPeriod: robot.TriggerPeriod);
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}
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/// <summary>
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/// 把兼容层输入数组转换成领域层 FlyshotProgram。
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/// </summary>
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/// <param name="name">轨迹名称。</param>
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/// <param name="waypoints">关节路点。</param>
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/// <param name="shotFlags">拍照标志。</param>
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/// <param name="offsetValues">偏移周期。</param>
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/// <param name="addressGroups">IO 地址组。</param>
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/// <returns>领域层飞拍程序。</returns>
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private static FlyshotProgram CreateProgram(
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string name,
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IEnumerable<IReadOnlyList<double>> waypoints,
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IEnumerable<bool> shotFlags,
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IEnumerable<int> offsetValues,
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IEnumerable<IReadOnlyList<int>> addressGroups)
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{
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return new FlyshotProgram(
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name: name,
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waypoints: waypoints.Select(static waypoint => new JointWaypoint(waypoint)).ToArray(),
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shotFlags: shotFlags.ToArray(),
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offsetValues: offsetValues.ToArray(),
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addressGroups: addressGroups.Select(static group => new IoAddressGroup(group)).ToArray());
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}
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/// <summary>
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/// 从规划轨迹和触发时间轴构造运行时可消费的稳定结果对象。
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/// </summary>
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/// <param name="plannedTrajectory">规划后的轨迹。</param>
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/// <param name="shotTimeline">触发时间轴。</param>
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/// <returns>运行时执行结果描述。</returns>
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private static TrajectoryResult CreateResult(
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PlannedTrajectory plannedTrajectory,
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ShotTimeline shotTimeline,
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bool usedCache,
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bool shapeTrajectoryEdges)
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{
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var denseJointTrajectory = TrajectorySampler.SampleJointTrajectory(
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plannedTrajectory,
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samplePeriod: plannedTrajectory.Robot.ServoPeriod.TotalSeconds,
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smoothStartStop: shapeTrajectoryEdges);
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return new TrajectoryResult(
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programName: plannedTrajectory.OriginalProgram.Name,
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method: plannedTrajectory.Method,
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isValid: true,
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duration: TimeSpan.FromSeconds(plannedTrajectory.WaypointTimes[^1]),
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shotEvents: shotTimeline.ShotEvents,
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triggerTimeline: shotTimeline.TriggerTimeline,
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artifacts: Array.Empty<TrajectoryArtifact>(),
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failureReason: null,
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usedCache: usedCache,
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originalWaypointCount: plannedTrajectory.OriginalWaypointCount,
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plannedWaypointCount: plannedTrajectory.PlannedWaypointCount,
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denseJointTrajectory: denseJointTrajectory);
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}
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/// <summary>
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/// 为飞拍执行生成一条平滑起停的时间轴。
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/// 保持路点位置不变，只重映射路点时刻，让起点和终点附近的速度自然收敛。
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/// </summary>
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private static PlannedTrajectory ApplySmoothStartStopTiming(PlannedTrajectory plannedTrajectory)
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{
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var originalTimes = plannedTrajectory.WaypointTimes;
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if (originalTimes.Count < 3)
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{
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return plannedTrajectory;
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}
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var totalDuration = originalTimes[^1];
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if (totalDuration <= 0.0)
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{
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return plannedTrajectory;
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}
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var smoothedTimes = new double[originalTimes.Count];
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smoothedTimes[0] = 0.0;
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smoothedTimes[^1] = totalDuration;
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for (var index = 1; index < originalTimes.Count - 1; index++)
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{
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var normalizedProgress = originalTimes[index] / totalDuration;
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smoothedTimes[index] = totalDuration * InvertSmoothStartStopProgress(normalizedProgress);
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}
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var segmentDurations = new double[smoothedTimes.Length - 1];
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for (var index = 0; index < segmentDurations.Length; index++)
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{
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segmentDurations[index] = smoothedTimes[index + 1] - smoothedTimes[index];
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}
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return new PlannedTrajectory(
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robot: plannedTrajectory.Robot,
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originalProgram: plannedTrajectory.OriginalProgram,
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plannedWaypoints: plannedTrajectory.PlannedWaypoints,
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waypointTimes: smoothedTimes,
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||
segmentDurations: segmentDurations,
|
||
segmentScales: plannedTrajectory.SegmentScales,
|
||
method: plannedTrajectory.Method,
|
||
iterations: plannedTrajectory.Iterations,
|
||
threshold: plannedTrajectory.Threshold);
|
||
}
|
||
|
||
/// <summary>
|
||
/// 反解 7 次 smootherstep 的时间进度，用二分法把原始线性进度映射成平滑时间轴。
|
||
/// </summary>
|
||
private static double InvertSmoothStartStopProgress(double normalizedProgress)
|
||
{
|
||
var target = Math.Clamp(normalizedProgress, 0.0, 1.0);
|
||
var low = 0.0;
|
||
var high = 1.0;
|
||
for (var iteration = 0; iteration < 40; iteration++)
|
||
{
|
||
var middle = (low + high) / 2.0;
|
||
var progress = EvaluateSmoothStartStopProgress(middle);
|
||
if (progress < target)
|
||
{
|
||
low = middle;
|
||
}
|
||
else
|
||
{
|
||
high = middle;
|
||
}
|
||
}
|
||
|
||
return (low + high) / 2.0;
|
||
}
|
||
|
||
/// <summary>
|
||
/// 计算 7 次 smootherstep 进度值，用于整段平滑起停时间律。
|
||
/// </summary>
|
||
private static double EvaluateSmoothStartStopProgress(double normalizedTime)
|
||
{
|
||
var u = Math.Clamp(normalizedTime, 0.0, 1.0);
|
||
var u2 = u * u;
|
||
var u3 = u2 * u;
|
||
var u4 = u3 * u;
|
||
var u5 = u4 * u;
|
||
var u6 = u5 * u;
|
||
var u7 = u6 * u;
|
||
return (35.0 * u4) - (84.0 * u5) + (70.0 * u6) - (20.0 * u7);
|
||
}
|
||
}
|