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

Sabetian, Saba 1 ; Looi, Thomas 1 ; Diller, Eric 2 ; Drake, James 1

1. Institute of Biomaterials and Biomedical Engineering, University of Toronto; 2. Department of Mechanical and Industrial Engineering, University of Toronto

Minimally invasive surgical procedures have gained popularity due to clinical benefits such as lower infection rates, less post-operative pain, faster recovery time, and smaller incisions. Concentric tube robots as shape-changing medical robots have the potential to allow for safer minimally invasive interventions at hard-to-reach sites of the human body. This is possible by curving around anatomical obstacles such as bones, blood vessels, and critical nerves. Many different designs and motion planning strategies for concentric tube robots (CTRs) have been proposed over the past 10 years, however, there are still two outstanding issues with the current design. First, although several studies on CTRs has shown that they are well suited in endoscopic surgical application, the field of view through the trocar is considerably limited. Second, there are many surgical procedures that require two tools simultaneously. These two arisen problems lead to the need of dual-arm concentric tube robots in the surgical development. Thus, design and development of a real-time, stable, and safe motion controller for dual-arm CTR to detect and avoid inter-collision between arms will be necessary. This study will not only benefit the development of minimally invasive surgical instruments by minimizing collision risks but also propose a fast and accurate motion planner for dual-arm CTRs to improve the surgical workflow of these medical robots. To avoid self-collision, a real-time control system using Differential Jacobian-based inverse kinematics is developed with three tasks with different priorities. The first prior task is joint-level constraints that accounts for unstable configurations. The second task is self-collision cost function and the last task is end-effector tracking. The proposed motion planner will be validated in both simulation and hardware modes to safely reach multiple target points in free workspace.