# Near-optimal Smooth Path Planning for Multisection Continuum Arms

## TL;DR

This paper introduces a new path planning algorithm for multisection continuum arms that guarantees finding a path if one exists, outperforming inverse kinematics in success rate, especially in obstacle-rich environments.

## Contribution

The paper presents a novel configuration graph-based path planning method for continuum arms, demonstrating completeness and efficiency through parallel computation.

## Key findings

- The proposed algorithm guarantees path existence detection in continuum arms.
- It outperforms inverse kinematics in success rate, especially with obstacles.
- Extensive tests validate the method's completeness and efficiency.

## Abstract

We study the path planning problem for continuum-arm robots, in which we are given a starting and an end point, and we need to compute a path for the tip of the continuum arm between the two points. We consider both cases where obstacles are present and where they are not. We demonstrate how to leverage the continuum arm features to introduce a new model that enables a path planning approach based on the configurations graph, for a continuum arm consisting of three sections, each consisting of three muscle actuators. The algorithm we apply to the configurations graph allows us to exploit parallelism in the computation to obtain efficient implementation. We conducted extensive tests, and the obtained results show the completeness of the proposed algorithm under the considered discretizations, in both cases where obstacles are present and where they are not. We compared our approach to the standard inverse kinematics approach. While the inverse kinematics approach is much faster when successful, our algorithm always succeeds in finding a path or reporting that no path exists, compared to a roughly 70% success rate of the inverse kinematics approach (when a path exists).