Robot Kinematics, Motion Planning and Control
This project focuses on building a practical robotics workflow from model-based kinematics to trajectory generation and closed-loop control. The work emphasizes stable motion quality, controllability, and reproducible simulation-based validation.
Project Goal
Develop a reliable pipeline for robot motion tasks by combining forward/inverse kinematics, collision-aware path generation, and controller tuning so that the manipulator can execute target trajectories safely and smoothly.
What I Did / My Contribution
- Formulated the robot kinematic model and validated workspace reachability.
- Implemented trajectory generation experiments and compared path smoothness metrics.
- Tested controller gains under different motion speeds and disturbance conditions.
- Documented the full experiment setup to support future extension and team reuse.
Methods / Workflow
- Build and verify kinematic chain assumptions and joint limits.
- Generate target waypoints and plan feasible joint-space or Cartesian trajectories.
- Apply control strategy and tune parameters with simulation feedback.
- Evaluate tracking error, smoothness, and robustness, then iterate.
Images / Videos / Simulation
Results / Takeaways
The final workflow improved trajectory consistency and provided a clear baseline for future integration with perception and higher-level task planning. The biggest takeaway was that early model validation and structured tuning significantly reduce downstream debugging time.
Tools / Skills
Kinematics, Motion Planning, Robot Control, Simulation, Parameter Tuning, Debugging