Self-Collision Detection and Avoidance for Dual-Arm Concentric Tube Robots

Abstract

Recent studies on concentric tube robots (CTRs) have shown that they are well-suited for minimally invasive endoscopic surgeries. However, typical surgical procedures require the use of multiple tools simultaneously which has led to the development of dual-arm CTRs that are susceptible to self-collision. In this paper, a closed-loop control system for dual-arm CTRs is proposed to detect and avoid the inter-collision between arms along their entire body. The collision detection module finds the minimum distance between the manipulators in the Cartesian space. To avoid self-collision, the proposed control system using differential Jacobian-based inverse kinematics is developed with three tasks with different priorities; physical constraints, self-collision avoidance, and end-effector tracking. The performance of the proposed control scheme is investigated through implementation for Cartesian control of a dual-arm CTR to reach pre-defined target points in a simulated scenario similar to epilepsy surgery. The self-collision detection module successfully predicted all 359 self-collision cases in the target region. The experimental results demonstrated the efficacy of the controller in handling inter-collision between arms over their entire body by keeping the minimum distance between arms at 1.542 mm.