REDUNDANCY-BASED OBSTACLE AVOIDANCE WITH VIRTUAL FORCE FIELDS FOR HIGH-DOF ROBOTIC ARM

This study presents an advanced control algorithm for obstacle avoidance in redundant robotic manipulators while maintaining accurate task execution, such as precise end-effector trajectory tracking. The proposed framework integrates Virtual Force Fields (VFF) with Null Space Projection to achieve real-time, collision-free motion without interfering with the robot’s primary objectives. The control system is based on a detailed dynamic model of a 6-degree-of-freedom (6-DOF) planar robot. Repulsive forces are computed from artificial potential fields and projected into the robot’s null space through an impedance-based control law. This enables the robot to perform self-motion adjustments to avoid obstacles while preserving end-effector performance. The effectiveness of the proposed method is validated through simulations in a dynamic environment with moving obstacles. Results demonstrate that the robot can accurately follow its desired trajectory, maintain low tracking errors, and generate compliant joint motions in response to external repulsive forces. The approach ensures dynamic stability, efficient obstacle avoidance, and high-fidelity task execution, highlighting its applicability in complex and unstructured environments.