During suturing tasks performed with minimally invasive surgical robots, configuration singularities and joint limits often force surgeons to interrupt the task and re-grasp the needle using dual-arm movements. This yields an increased operator's cognitive load, time-to-completion and performance degradation. In this paper, we propose a haptic-guided shared control method for grasping the needle with the Patient Side Manipulator (PSM) of the da Vinci robot avoiding such issues. We suggest a cost function consisting of (i) the distance from robot joint limits and (ii) the task-oriented manipulability along the suturing trajectory. Evaluating the cost and its gradient on the needle grasping manifold allows us to obtain the optimal grasping pose for joint-limit and singularity free robot movements during suturing. We compute force cues and display them through the Master Tool Manipulator (MTM) to guide the surgeon towards the optimal grasp. As such, our system helps the operator to choose a grasping configuration that allows the robot to avoid joint limits and singularities during postgrasp suturing movements. We show the effectiveness of the proposed haptic-guided shared control method during suturing using both simulated and real experiments. The results illustrate that our approach significantly improves the performance in terms of needle re-grasping.
Selvaggio et al. REF proposed a haptic-guided shared control for needle grasping that significantly improved needle re-grasping performance.
Haptic-guided shared control for needle grasping optimization in minimally invasive robotic surgery
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Computer Science