Optimal Multi-Manipulator Arm Placement for Maximal Dexterity during Robotics Surgery

TL;DR

This paper presents a method to optimize the placement of multiple robotic arms in surgery to maximize dexterity, minimize collisions, and improve reachability, using scoring functions and fast evaluation techniques.

Contribution

It introduces a novel optimization approach for robotic arm placement that accounts for collision avoidance and reachability, applicable to various surgical robotic systems.

Findings

Optimized arm placements reduce collisions during surgery.

The method improves surgeon reachability within the patient.

Optimization results are validated on canonical trajectories.

Abstract

Robot arm placements are oftentimes a limitation in surgical preoperative procedures, relying on trained staff to evaluate and decide on the optimal positions for the arms. Given new and different patient anatomies, it can be challenging to make an informed choice, leading to more frequently colliding arms or limited manipulator workspaces. In this paper, we develop a method to generate the optimal manipulator base positions for the multi-port da Vinci surgical system that minimizes self-collision and environment-collision, and maximizes the surgeon's reachability inside the patient. Scoring functions are defined for each criterion so that they may be optimized over. Since for multi-manipulator setups, a large number of free parameters are available to adjust the base positioning of each arm, a challenge becomes how one can expediently assess possible setups. We thus also propose methods that perform fast queries of each measure with the use of a proxy collision-checker. We then develop an optimization method to determine the optimal position using the scoring functions. We evaluate the optimality of the base positions for the robot arms on canonical trajectories, and show that the solution yielded by the optimization program can satisfy each criterion. The metrics and optimization strategy are generalizable to other surgical robotic platforms so that patient-side manipulator positioning may be optimized and solved.