IMU Operations

This guide covers IMU (Inertial Measurement Unit) operations, setup, and troubleshooting for the RCR Common Robotics Platform.

Overview

The robot uses an IMU for orientation sensing, motion detection, and navigation. The IMU provides acceleration, angular velocity, and orientation data.

IMU Specifications

  • Model: MPU9250

  • Accelerometer: ±16g range

  • Gyroscope: ±2000°/s range

  • Magnetometer: ±4800μT range

  • Interface: I2C

  • Update Rate: 100 Hz

IMU Setup

1. Hardware Connection

  1. Physical Mounting

    • Mount IMU in stable location

    • Minimize vibration

    • Ensure proper orientation

  2. Power Connection

    • Connect to robot power system

    • Verify voltage requirements (3.3V)

    • Check for proper grounding

  3. Data Connection

    • Connect to I2C bus

    • Verify pull-up resistors

    • Test communication

2. Software Configuration

Launch IMU:

# Launch IMU node
ros2 launch common_platform imu.launch.py

Verify Data:

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

# Monitor data rate
ros2 topic hz /${ROS_NAME}/imu/data

IMU Calibration

1. Static Calibration

Calibration Process:

  1. Place robot on level surface

  2. Ensure no movement

  3. Run calibration procedure

  4. Save calibration parameters

Calibration Command:

# Run IMU calibration
ros2 run imu_calibration calibrate_imu

2. Dynamic Calibration

Motion Calibration:

  • Perform controlled movements

  • Calibrate gyroscope bias

  • Verify acceleration readings

Orientation Calibration:

  • Align with known orientation

  • Calibrate magnetometer

  • Verify heading accuracy

IMU Data Analysis

1. Data Structure

IMU Message:

std_msgs/Header header
geometry_msgs/Quaternion orientation
float64[9] orientation_covariance
geometry_msgs/Vector3 angular_velocity
float64[9] angular_velocity_covariance
geometry_msgs/Vector3 linear_acceleration
float64[9] linear_acceleration_covariance

2. Data Quality

Check Data Quality:

# Monitor IMU data
ros2 topic echo /imu/data

# Check for:
# - Stable orientation
# - Reasonable acceleration values
# - Consistent angular velocity

IMU Applications

1. Orientation Sensing

Quaternion Data:

  • Use for robot orientation

  • Implement orientation control

  • Monitor attitude changes

Euler Angles:

  • Convert for human readability

  • Use for control algorithms

  • Monitor pitch, roll, yaw

2. Motion Detection

Acceleration Data:

  • Detect motion changes

  • Implement motion control

  • Monitor for impacts

Angular Velocity:

  • Detect rotation

  • Implement rotation control

  • Monitor for spinning

Troubleshooting

Common Issues

No IMU Data:

  • Check I2C connection

  • Verify power supply

  • Check device address

  • Test with I2C tools

Poor Data Quality:

  • Check mounting stability

  • Verify calibration

  • Test in different environments

  • Check for interference

Drift Issues:

  • Recalibrate IMU

  • Check for temperature effects

  • Verify mounting

  • Test with known orientations

Diagnostic Commands

# Check I2C devices
i2cdetect -y 1

# Test I2C communication
i2cget -y 1 0x68 0x75

# Monitor data quality
ros2 topic echo /imu/data
ros2 topic hz /imu/data

Error Codes

Common Error Messages:

  • “Failed to open I2C device” - Check I2C connection

  • “No data received” - Check power and connections

  • “Invalid data” - Check for interference or damage

Maintenance

Regular Maintenance

Daily:

  • Visual inspection

  • Check for vibration

  • Verify data quality

Weekly:

  • Check mounting stability

  • Test calibration

  • Monitor performance

Monthly:

  • Full calibration check

  • Performance testing

  • Connection inspection

Cleaning Procedures

IMU Unit:

  1. Power off robot

  2. Clean mounting surface

  3. Check for loose connections

  4. Verify stability

Mounting Area:

  • Clean mounting surface

  • Check for loose connections

  • Verify stability

Performance Optimization

Data Processing

Filtering:

  • Remove noise from data

  • Implement low-pass filters

  • Smooth data for better performance

Sensor Fusion:

  • Combine with other sensors

  • Use Kalman filters

  • Improve accuracy

Parameter Tuning

IMU Parameters:

# In launch file
update_rate: 100
linear_acceleration_stddev: 0.01
angular_velocity_stddev: 0.01

Filter Parameters:

  • Adjust filter gains

  • Balance performance vs. accuracy

  • Consider computational load

Safety Considerations

Operating Safety

  • Handle with care during maintenance

  • Follow manufacturer guidelines

  • Consider temperature effects

  • Monitor for failures

Data Safety

  • Verify data accuracy

  • Handle sensor failures gracefully

  • Implement appropriate logging

  • Consider data validation

For LiDAR operations, see LiDAR Operations For camera operations, see Camera Operations For troubleshooting, see Troubleshooting