A · Robotics Systems Engineering
Engineering Guides
Step-by-step guides for selecting, configuring, integrating and validating robotics hardware and software.
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01 Robotics System Architecture & Requirements
02 Sensor Selection, Trade-offs & Integration
- Sensor combination: camera + IMU
- Sensor combination: LiDAR + IMU
- Sensor combination: camera + LiDAR
- Sensor combination: GNSS + IMU
- Sensor combination: encoder + IMU
- Sensor combination: GNSS + IMU + LiDAR
- Sensor combination: camera + LiDAR + radar
- Mounting, interfaces, ROS 2 drivers and validation checklist
03 Actuators, Motors, Electrical & Power Integration
04 Embedded Systems & Hardware Interfaces
05 Onboard Computer, CPU/GPU Selection & Compute Sizing
06 Camera–LiDAR Calibration & Coordinate Transformations
- Frame conventions and transform direction
- Transforming points between camera, LiDAR and base frames
- Projecting LiDAR points into the image
- Camera–LiDAR extrinsic calibration and validation
- LiDAR–IMU and camera–IMU calibration
- TF2 in ROS 2: static transforms and debugging
- Associating detections with LiDAR clusters
07 Sensor Time Synchronization & Latency Engineering
08 Robotics Perception & Sensor Integration
09 SLAM Selection, Configuration & Troubleshooting
10 Visual-Inertial SLAM & LiDAR-Inertial Integration
11 Sensor Fusion & State Estimation
12 Outdoor-to-Indoor Localization & GNSS-Denied Navigation
13 Navigation Stack & Autonomous Motion Planning
14 Motion Control & Actuator Integration
- Tuning PID on a real robot
- Calibrating wheel radius, separation and encoders
- Diagnosing oscillation, saturation and slip
- Integrating a controller with ros2_control
- Validating controller performance
- Balance basics: the zero moment point and the inverted pendulum
- Whole-body control: tasks, priorities and the null space
- Model predictive control for robots: horizon, constraints and solve time