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

Saba Sabetian, Thomas Looi, Eric Diller, James M. Drake

发表年份
2019
引用次数
11

摘要

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.

关键词

Collision detectionConcentricCollisionCartesian coordinate systemKinematicsComputer scienceInverse kinematicsCollision avoidanceRobotic armTrajectory

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