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第八章作业

作业要求

实现融合运动模型的滤波方法

可以仿照CorrectErrorEstimationPoseVel中的给CorrectErrorEstimationPose加上运动模型约束

running

  • Test1

    error_state_kalman_filter:
      earth:
          # gravity can be calculated from https://www.sensorsone.com/local-gravity-calculator/ using latitude and height:
          gravity_magnitude: 9.80943
          # rotation speed, rad/s:
          rotation_speed: 7.292115e-5
          # latitude:
          latitude:   48.9827703173
      covariance:
          prior:
              pos: 1.0e-6
              vel: 1.0e-6
              ori: 1.0e-6
              epsilon: 1.0e-6
              delta: 1.0e-6
          process:
              gyro: 1.0e-4
              accel: 2.5e-3
          measurement:
              pose:
                  pos: 1.0e-4
                  ori: 1.0e-4
              pos: 1.0e-4
              vel: 2.5e-3
      motion_constraint: 
          activated: true
          w_b_thresh: 0.13
    APE laser fused
    max 2.706153 2.783004
    mean 1.750127 1.751943
    median 1.728464 1.731996
    min 1.000020 0.891633
    rmse 1.759152 1.762624
    sse 13607.027875 13660.785561
    std 0.177962 0.193746
  • Test2

    error_state_kalman_filter:
      earth:
          # gravity can be calculated from https://www.sensorsone.com/local-gravity-calculator/ using latitude and height:
          gravity_magnitude: 9.80943
          # rotation speed, rad/s:
          rotation_speed: 7.292115e-5
          # latitude:
          latitude:   48.9827703173
      covariance:
          prior:
              pos: 1.0e-6
              vel: 1.0e-6
              ori: 1.0e-6
              epsilon: 1.0e-6
              delta: 1.0e-6
          process:
              gyro: 1.0e-4
              accel: 2.5e-3
          measurement:
              pose:
                  pos: 1.0e-3   # x10
                  ori: 1.0e-3   # x10
              pos: 1.0e-3       # x10
              vel: 2.5e-3
      motion_constraint: 
          activated: true
          w_b_thresh: 0.13
    APE laser fused
    max 1.847445 1.890410
    mean 0.902068 0.917762
    median 0.873098 0.892060
    min 0.367366 0.358313
    rmse 0.919268 0.937960
    sse 3708.941335 3861.305624
    std 0.176994 0.193600

实现gps位置和编码器的滤波融合

这个好像第八章作业框架代码已经实现了啊

配置文件里选择position_velocity融合策略

  • gnss gnss
  • fused fused