Files
ParkingRobot/MultiWheelC/StateEstimation/VelocityEstimator2D.cs
T
2026-08-14 13:55:19 +08:00

183 lines
6.1 KiB
C#

using System;
using MyParking.Shared;
namespace MultiWheelC.StateEstimation
{
/// <summary>
/// 根据连续有效的Detour世界位姿和真实时间差估算车辆二维速度。
/// </summary>
public sealed class VelocityEstimator2D
{
public const double DefaultLinearFilterTimeConstantSeconds =
0.15;
public const double DefaultAngularFilterTimeConstantSeconds =
0.20;
private readonly FirstOrderLowPassFilter
_worldVelocityXFilter;
private readonly FirstOrderLowPassFilter
_worldVelocityYFilter;
private readonly FirstOrderLowPassFilter
_angularVelocityFilter;
private bool _hasPreviousSample;
private Pose2D _previousPoseInWorld;
private double _previousTimestampSeconds;
/// <summary>
/// 创建使用默认0.15s线速度和0.20s角速度时间常数的估计器。
/// </summary>
public VelocityEstimator2D()
: this(
DefaultLinearFilterTimeConstantSeconds,
DefaultAngularFilterTimeConstantSeconds)
{
}
/// <summary>
/// 创建使用指定线速度和角速度滤波时间常数的估计器。
/// </summary>
public VelocityEstimator2D(
double linearFilterTimeConstantSeconds,
double angularFilterTimeConstantSeconds)
{
_worldVelocityXFilter =
new FirstOrderLowPassFilter(
linearFilterTimeConstantSeconds);
_worldVelocityYFilter =
new FirstOrderLowPassFilter(
linearFilterTimeConstantSeconds);
_angularVelocityFilter =
new FirstOrderLowPassFilter(
angularFilterTimeConstantSeconds);
}
/// <summary>
/// 使用一个新的有效定位样本更新并返回车辆状态。
/// </summary>
public VehicleState Update(
Pose2D poseInWorld,
double sampleTimestampSeconds)
{
NumericGuard.EnsureFinite(
poseInWorld,
nameof(poseInWorld));
NumericGuard.EnsureFiniteNonNegative(
sampleTimestampSeconds,
nameof(sampleTimestampSeconds));
var normalizedPoseInWorld =
new Pose2D(
poseInWorld.XMeters,
poseInWorld.YMeters,
AngleMath.NormalizeRadians(
poseInWorld.YawRadians));
if (!_hasPreviousSample)
{
return Reset(
normalizedPoseInWorld,
sampleTimestampSeconds);
}
var deltaTimeSeconds =
sampleTimestampSeconds -
_previousTimestampSeconds;
if (deltaTimeSeconds <= 0.0)
{
throw new ArgumentOutOfRangeException(
nameof(sampleTimestampSeconds),
"新定位样本的单调时间戳必须严格大于上一帧。");
}
var rawVelocityXInWorld =
(normalizedPoseInWorld.XMeters -
_previousPoseInWorld.XMeters) /
deltaTimeSeconds;
var rawVelocityYInWorld =
(normalizedPoseInWorld.YMeters -
_previousPoseInWorld.YMeters) /
deltaTimeSeconds;
var rawAngularVelocity =
AngleMath.ShortestDifferenceRadians(
normalizedPoseInWorld.YawRadians,
_previousPoseInWorld.YawRadians) /
deltaTimeSeconds;
var filteredTwistInWorld =
new Twist2D(
_worldVelocityXFilter.Update(
rawVelocityXInWorld,
deltaTimeSeconds),
_worldVelocityYFilter.Update(
rawVelocityYInWorld,
deltaTimeSeconds),
_angularVelocityFilter.Update(
rawAngularVelocity,
deltaTimeSeconds));
_previousPoseInWorld =
normalizedPoseInWorld;
_previousTimestampSeconds =
sampleTimestampSeconds;
return new VehicleState(
sampleTimestampSeconds,
normalizedPoseInWorld,
filteredTwistInWorld,
true);
}
/// <summary>
/// 使用当前定位重新建立差分基准,并返回速度无效的零速状态。
/// </summary>
public VehicleState Reset(
Pose2D poseInWorld,
double sampleTimestampSeconds)
{
NumericGuard.EnsureFinite(
poseInWorld,
nameof(poseInWorld));
NumericGuard.EnsureFiniteNonNegative(
sampleTimestampSeconds,
nameof(sampleTimestampSeconds));
_previousPoseInWorld =
new Pose2D(
poseInWorld.XMeters,
poseInWorld.YMeters,
AngleMath.NormalizeRadians(
poseInWorld.YawRadians));
_previousTimestampSeconds =
sampleTimestampSeconds;
_hasPreviousSample = true;
_worldVelocityXFilter.Reset();
_worldVelocityYFilter.Reset();
_angularVelocityFilter.Reset();
return new VehicleState(
sampleTimestampSeconds,
_previousPoseInWorld,
Twist2D.Zero,
false);
}
/// <summary>
/// 清除差分基准和全部滤波历史,使下一帧重新初始化估计器。
/// </summary>
public void Reset()
{
_hasPreviousSample = false;
_previousPoseInWorld = Pose2D.Identity;
_previousTimestampSeconds = 0.0;
_worldVelocityXFilter.Reset();
_worldVelocityYFilter.Reset();
_angularVelocityFilter.Reset();
}
}
}