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d8b25bad77
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feat: VESC CAN odometry for nav2 (Issue #646)
Replace single-motor vesc_odometry_bridge with dual-CAN differential
drive odometry for left (CAN 61) and right (CAN 79) VESC motors.
New files:
- diff_drive_odom.py: pure-Python kinematics (eRPM→wheel vel, exact arc
integration, heading wrap), no ROS deps, fully unit-tested
- test/test_vesc_odometry.py: 20 unit tests (straight, arc, spin,
invert_right, guard conditions) — all pass
- config/vesc_odometry_params.yaml: configurable wheel_radius,
wheel_separation, motor_poles, invert_right, covariance tuning
Updated:
- vesc_odometry_bridge.py: rewritten as VESCCANOdometryNode; subscribes
to /vesc/can_61/state and /vesc/can_79/state (std_msgs/String JSON);
publishes /odom and /saltybot/wheel_odom (nav_msgs/Odometry) + TF
odom→base_link with proper 6×6 covariance matrices
- odometry_bridge.launch.py: updated to launch vesc_can_odometry with
vesc_odometry_params.yaml
- setup.py: added vesc_can_odometry entry point + config install
- pose_fusion_node.py: added optional wheel_odom_topic subscriber that
feeds DiffDriveOdometry velocities into EKF via update_vo_velocity
- pose_fusion_params.yaml: added use_wheel_odom, wheel_odom_topic,
sigma_wheel_vel_m_s, sigma_wheel_omega_r_s parameters
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-03-17 09:54:19 -04:00 |
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c76d5b0dd7
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feat: Multi-sensor pose fusion node (Issue #595)
New package saltybot_pose_fusion — EKF fusing UWB+IMU absolute pose,
visual odometry velocity, and raw IMU into a single authoritative pose.
pose_fusion_ekf.py (pure Python, no ROS2 deps):
PoseFusionEKF — state [x, y, θ, vx, vy, ω], 6-state EKF.
- predict_imu(ax_body, ay_body, omega, dt): body-frame IMU predict step
with Jacobian F, bias-compensated accel, process noise Q.
- update_uwb_position(x, y, sigma_m): absolute position measurement
(H=[1,0,0,0,0,0; 0,1,0,0,0,0]) from UWB+IMU fused stream.
- update_uwb_heading(heading_rad, sigma_rad): heading measurement.
- update_vo_velocity(vx_body, omega, ...): VO velocity measurement —
body-frame vx rotated to world via cos/sin(θ), updates [vx,vy,ω] state.
- Joseph-form covariance update for numerical stability.
- Dual dropout clocks: uwb_dropout_s, vo_dropout_s (reset on each update).
- Velocity damping when uwb_dropout_s > 2s.
- Sensor weight parameters: sigma_uwb_pos_m, sigma_uwb_head_rad,
sigma_vo_vel_m_s, sigma_vo_omega_r_s, sigma_imu_accel/gyro,
sigma_vel_drift, dropout_vel_damp.
pose_fusion_node.py (ROS2 node 'pose_fusion'):
- Subscribes: /imu/data (Imu, 200Hz → predict), /saltybot/pose/fused_cov
(PoseWithCovarianceStamped, 10Hz → position+heading update, σ extracted
from message covariance when use_uwb_covariance=true), /saltybot/visual_odom
(Odometry, 30Hz → velocity update, σ from twist covariance).
- Publishes: /saltybot/pose/authoritative (PoseWithCovarianceStamped),
/saltybot/pose/status (String JSON, 10Hz).
- TF2: map→base_link broadcast at IMU rate.
- Suppresses output when uwb_dropout_s > uwb_dropout_max_s (10s).
- Warns (throttled) on UWB/VO dropout.
config/pose_fusion_params.yaml: sensor weights + dropout thresholds.
launch/pose_fusion.launch.py: single node launch with params_file arg.
test/test_pose_fusion_ekf.py: 13 unit tests — init, predict, UWB/VO
updates, dropout reset, covariance shape/convergence, sigma override.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-03-14 15:00:54 -04:00 |
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