Obstacle Avoidance Path Planning for Robotic Arm Based on EIT Tactile Sensing

This study introduces a novel flexible tactile sensor using electrical impedance tomography (EIT) for tactile sensing and integrates it into a robotic arm to enable it to have tactile sensing capabilities. In order to enable the robot to autonomously perform interactive operations in an unstructured open environment, this paper proposes a path planning algorithm based on the artificial potential field method in combination with the above-mentioned tactile sensor to achieve autonomous obstacle avoidance of the robotic arm. Specifically, a repulsive potential field is proposed, which is adjusted according to the height of the robotic arm to guide it around detected obstacles. In order to verify the effectiveness of the proposed flexible tactile sensor and obstacle avoidance path planning strategy, the designed tactile sensor and obstacle avoidance algorithm were integrated into the UR5 robotic arm platform for experimental verification. The experimental results show that the robotic arm can accurately detect tactile targets in the environment, and can autonomously adjust the motion path in real time according to the environment, realizing autonomous and safe interaction of the robotic arm in actual scenarios. This study helps to improve the autonomy and operational safety of robots in complex environments, and has important theoretical and practical significance in the field of robot tactile perception and obstacle avoidance navigation.