Calibration Procedures

This guide covers the calibration procedures for sensors and systems on the RCR Common Robotics Platform.

Prerequisites

  • Hardware and software setup completed

  • Robot in a stable, level environment

  • Calibration tools (ruler, level, etc.)

  • Access to robot console/terminal

IMU Calibration

1. Static Calibration

# Launch robot with IMU
ros2 launch common_platform launch_robot.launch.py

# Monitor IMU data
ros2 topic echo /${ROS_NAME}/imu/data

2. Calibration Steps

  1. Level the Robot

    • Place robot on level surface

    • Ensure no movement during calibration

  2. Run Calibration

    # Use calibration tool
ros2 run imu_calibration calibrate_imu

  3. Verify Results

    • Check for zero bias values

    • Verify stable readings

LiDAR Calibration

1. Mounting Verification

  • Ensure LiDAR is level

  • Check for obstructions

  • Verify mounting stability

2. Range Calibration

# Monitor LiDAR data
ros2 topic echo /${ROS_NAME}/scan

# Check for consistent readings
ros2 run rqt_plot rqt_plot /${ROS_NAME}/scan/ranges

3. Angular Calibration

  • Verify 360° coverage

  • Check for blind spots

  • Test at different distances

Camera Calibration

1. Intrinsic Calibration

# Launch camera
ros2 launch common_platform camera.launch.py

# Run calibration
ros2 run camera_calibration cameracalibrator --size 8x6 --square 0.108 image:=/camera/image_raw camera:=/camera

2. Extrinsic Calibration

  • Align camera with robot frame

  • Verify coordinate transformations

  • Test with known objects

Motor Calibration

1. Encoder Calibration

# Test encoder counts
ros2 topic echo /${ROS_NAME}/wheel_odom

# Verify counts per revolution
ros2 run motor_calibration calibrate_encoders

2. PID Tuning

# Launch motor control
ros2 launch common_platform motor_control.launch.py

# Tune PID parameters
ros2 run rqt_reconfigure rqt_reconfigure

Odometry Calibration

1. Wheel Diameter

  • Measure actual wheel diameter

  • Update configuration parameters

  • Test with known distances

2. Wheelbase

  • Measure distance between wheels

  • Update robot description

  • Verify turning radius

System Integration

1. Coordinate Frames

# Check transform tree
ros2 run tf2_tools view_frames

# Verify frame relationships
ros2 run tf2_ros tf2_echo base_link laser_link

2. Sensor Fusion

  • Verify sensor data alignment

  • Check for timing issues

  • Test data consistency

Calibration Verification

1. Static Tests

  • Robot should report zero velocity when stationary

  • IMU should show level orientation

  • LiDAR should show consistent environment

2. Dynamic Tests

  • Move robot known distances

  • Verify odometry accuracy

  • Test sensor data during movement

Troubleshooting

Common Issues

IMU Drift

  • Check mounting stability

  • Verify calibration parameters

  • Consider temperature effects

LiDAR Inconsistencies

  • Check for obstructions

  • Verify mounting alignment

  • Test in different environments

Odometry Errors

  • Verify encoder connections

  • Check wheel diameter measurements

  • Test on different surfaces

Maintenance

Regular Calibration

  • Monthly IMU calibration

  • Quarterly LiDAR verification

  • Annual full system calibration

Documentation

  • Record calibration values

  • Note environmental conditions

  • Track performance over time

For hardware setup, see Hardware Setup For software setup, see Software Setup For troubleshooting, see Troubleshooting