IK-driven manipulation with dynamic visual object tracking
This project demonstrates a real-time vision-guided robotic arm simulation where a multi-DOF manipulator tracks and reaches for dynamically moving objects using computer vision input. An Inverse Kinematics solver maps Cartesian coordinates from visual detections directly to joint-space configurations, enabling precise and responsive end-effector positioning.
A continuous control loop updates target trajectories based on live object tracking data, minimizing steady-state error and ensuring smooth, collision-free motion. The simulation validates workspace constraints and joint limits before hardware deployment, bridging the gap between algorithmic development and physical robot control.