yunxiao.zhu
4eeaa3fef3
* 建立 .NET 8 解决方案及分层项目结构 * 添加 Flyshot.Core.Domain 领域模型（机器人、轨迹、运动学） * 添加 Flyshot.Core.Planning 规划层（ICSP、CubicSpline、采样器） * 添加 Flyshot.Core.Triggering 触发时序与 IO 时间轴 * 添加 Flyshot.Core.Config 配置兼容与 .robot 解析 * 添加 Flyshot.Server.Host 最小宿主及 /healthz 端点 * 补充单元测试与集成测试项目 * 添加 CLAUDE.md、AGENTS.md、README.md 项目规范
228 lines
8.8 KiB
C#
228 lines
8.8 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.Triggering;
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namespace Flyshot.Core.Tests;
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/// <summary>
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/// 锁定 Task 4 的最小兼容面，覆盖 ICSP、自适应补点以及飞拍触发时间轴。
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/// </summary>
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public sealed class PlanningCompatibilityTests
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{
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/// <summary>
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/// 验证 ICSP 规划至少会生成严格递增的 waypoint 时间轴。
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/// </summary>
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[Fact]
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public void ICspPlanner_ReturnsMonotonicWaypointTimes()
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{
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var request = new TrajectoryRequest(
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robot: CreateRobotProfile([1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 2, 2], [10, 10, 10, 10, 10, 10]),
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program: CreateProgram(
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new[]
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{
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new[] { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 },
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new[] { 0.4, 0.1, 0.0, 0.0, 0.0, 0.0 },
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new[] { 0.8, 0.3, 0.0, 0.0, 0.0, 0.0 },
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new[] { 1.0, 0.2, 0.0, 0.0, 0.0, 0.0 }
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}),
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method: PlanningMethod.Icsp);
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var trajectory = new ICspPlanner().Plan(request);
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Assert.Equal(4, trajectory.WaypointTimes.Count);
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Assert.All(trajectory.WaypointTimes.Zip(trajectory.WaypointTimes.Skip(1)), pair => Assert.True(pair.Second > pair.First));
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}
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/// <summary>
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/// 验证 speed09 风格的大跳变样本在 self-adapt-icsp 下会通过补中点收敛。
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/// </summary>
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[Fact]
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public void SelfAdaptIcspPlanner_InsertsMidpoints_ForEol9Case()
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{
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var workspaceRoot = GetWorkspaceRoot();
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var configPath = Path.Combine(workspaceRoot, "Rvbust", "EOL9 EAU 90", "eol9_eau_90.json");
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var modelPath = Path.Combine(workspaceRoot, "FlyingShot", "FlyingShot", "Models", "LR_Mate_200iD_7L.robot");
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var config = new RobotConfigLoader().Load(configPath);
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var baseProfile = new RobotModelLoader().LoadProfile(modelPath, config.Robot.AccLimitScale, config.Robot.JerkLimitScale);
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var constrainedProfile = ScaleRobotProfile(baseProfile, velocityScale: 0.9, accelerationScale: 0.9 * 0.9, jerkScale: 0.9 * 0.9 * 0.9);
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var request = new TrajectoryRequest(
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robot: constrainedProfile,
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program: config.Programs["EOL9_EAU_90"],
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method: PlanningMethod.SelfAdaptIcsp);
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var trajectory = new SelfAdaptIcspPlanner().Plan(request, adaptIcspTryNum: config.Robot.AdaptIcspTryNum);
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Assert.True(trajectory.InsertedWaypointCount > 0);
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Assert.True(trajectory.PlannedWaypointCount > trajectory.OriginalWaypointCount);
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Assert.True(trajectory.SegmentScales.Max() <= 1.0005);
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}
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/// <summary>
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/// 验证补点后仍然能按原始示教点顺序找回时间戳，而不是错误地绑定到新增中点。
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/// </summary>
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[Fact]
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public void WaypointTimestampResolver_UsesOriginalTeachPointsAfterInsertion()
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{
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var originalProgram = CreateProgram(
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new[]
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{
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new[] { 0.0, 0.0 },
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new[] { 1.0, 0.0 },
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new[] { 2.0, 0.0 },
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new[] { 3.0, 0.0 }
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});
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var trajectory = new PlannedTrajectory(
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robot: CreateRobotProfile([1, 1], [1, 1], [1, 1]),
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originalProgram: originalProgram,
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plannedWaypoints:
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[
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new JointWaypoint([0.0, 0.0]),
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new JointWaypoint([0.5, 0.0]),
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new JointWaypoint([1.0, 0.0]),
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new JointWaypoint([2.0, 0.0]),
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new JointWaypoint([2.5, 0.0]),
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new JointWaypoint([3.0, 0.0])
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],
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waypointTimes: [0.0, 0.25, 0.5, 1.0, 1.5, 2.0],
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segmentDurations: [0.25, 0.25, 0.5, 0.5, 0.5],
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segmentScales: [1.0, 1.0, 1.0, 1.0, 1.0],
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method: PlanningMethod.SelfAdaptIcsp,
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iterations: 3,
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threshold: 0.0);
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var timestamps = new WaypointTimestampResolver().Resolve(trajectory);
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Assert.Equal([0.0, 0.5, 1.0, 2.0], timestamps);
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}
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/// <summary>
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/// 验证触发时间轴会使用原始 waypoint 时间、offset 周期和地址组生成 ShotEvent/TrajectoryDoEvent。
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/// </summary>
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[Fact]
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public void ShotTimelineBuilder_MapsOffsetsToShotEventsAndTriggerTimeline()
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{
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var robot = CreateRobotProfile([1, 1], [1, 1], [1, 1]);
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var program = new FlyshotProgram(
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name: "demo",
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waypoints:
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[
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new JointWaypoint([0.0, 0.0]),
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new JointWaypoint([1.0, 0.0]),
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new JointWaypoint([2.0, 0.0])
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],
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shotFlags: [false, true, false],
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offsetValues: [0, 1, 0],
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addressGroups:
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[
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new IoAddressGroup(Array.Empty<int>()),
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new IoAddressGroup([2, 4]),
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new IoAddressGroup(Array.Empty<int>())
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]);
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var trajectory = new PlannedTrajectory(
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robot: robot,
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originalProgram: program,
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plannedWaypoints: program.Waypoints,
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waypointTimes: [0.0, 0.5, 1.0],
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segmentDurations: [0.5, 0.5],
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segmentScales: [1.0, 1.0],
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method: PlanningMethod.Icsp,
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iterations: 1,
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threshold: 0.0);
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var timeline = new ShotTimelineBuilder(new WaypointTimestampResolver())
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.Build(trajectory, holdCycles: 2, samplePeriod: TimeSpan.FromMilliseconds(16));
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var shotEvent = Assert.Single(timeline.ShotEvents);
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Assert.Equal(0.508, shotEvent.TriggerTime, precision: 3);
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Assert.Equal([2, 4], shotEvent.AddressGroup.Addresses);
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var doEvent = Assert.Single(timeline.TriggerTimeline);
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Assert.Equal(1, doEvent.WaypointIndex);
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Assert.Equal(1, doEvent.OffsetCycles);
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Assert.Equal(2, doEvent.HoldCycles);
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}
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/// <summary>
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/// 构造一个最小 RobotProfile，便于规划层单元测试聚焦在时间轴逻辑上。
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/// </summary>
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private static RobotProfile CreateRobotProfile(
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IReadOnlyList<double> velocityLimits,
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IReadOnlyList<double> accelerationLimits,
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IReadOnlyList<double> jerkLimits)
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{
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return new RobotProfile(
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name: "TestRobot",
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modelPath: "Models/Test.robot",
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degreesOfFreedom: velocityLimits.Count,
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jointLimits: velocityLimits
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.Select((velocity, index) => new JointLimit(
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$"J{index + 1}",
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velocity,
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accelerationLimits[index],
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jerkLimits[index]))
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.ToArray(),
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jointCouplings: Array.Empty<JointCoupling>(),
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servoPeriod: TimeSpan.FromMilliseconds(8),
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triggerPeriod: TimeSpan.FromMilliseconds(8));
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}
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/// <summary>
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/// 构造一个默认不带拍照点的最小 FlyshotProgram。
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/// </summary>
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private static FlyshotProgram CreateProgram(IEnumerable<double[]> waypointRows)
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{
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var rows = waypointRows.ToArray();
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return new FlyshotProgram(
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name: "demo",
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waypoints: rows.Select(row => new JointWaypoint(row)).ToArray(),
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shotFlags: Enumerable.Repeat(false, rows.Length).ToArray(),
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offsetValues: Enumerable.Repeat(0, rows.Length).ToArray(),
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addressGroups: Enumerable.Range(0, rows.Length).Select(_ => new IoAddressGroup(Array.Empty<int>())).ToArray());
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}
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/// <summary>
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/// 在不丢失 couple 元数据的前提下，按比例缩放机器人关节限制。
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/// </summary>
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private static RobotProfile ScaleRobotProfile(RobotProfile source, double velocityScale, double accelerationScale, double jerkScale)
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{
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return new RobotProfile(
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name: source.Name,
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modelPath: source.ModelPath,
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degreesOfFreedom: source.DegreesOfFreedom,
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jointLimits: source.JointLimits
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.Select(limit => new JointLimit(
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limit.JointName,
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limit.VelocityLimit * velocityScale,
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limit.AccelerationLimit * accelerationScale,
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limit.JerkLimit * jerkScale))
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.ToArray(),
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jointCouplings: source.JointCouplings,
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servoPeriod: source.ServoPeriod,
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triggerPeriod: source.TriggerPeriod);
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}
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/// <summary>
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/// 定位父工作区根目录，读取真实的 EOL9 样本和机器人模型。
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/// </summary>
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private static string GetWorkspaceRoot()
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{
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var current = new DirectoryInfo(AppContext.BaseDirectory);
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while (current is not null)
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{
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if (File.Exists(Path.Combine(current.FullName, "FlyshotReplacement.sln")))
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{
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return Path.GetFullPath(Path.Combine(current.FullName, ".."));
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}
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current = current.Parent;
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}
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throw new DirectoryNotFoundException("Unable to locate the flyshot workspace root.");
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}
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}
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