Optimal Design of Continuum Robots with Reachability Constraints

This paper presents a method developed to find the optimal design of soft robots considering reachability constraint. It demonstrates the application of generative design in the emerging field of soft robots. It also shows a novel kinematics model and reachability computation techniques for soft robots.

Abstract

Optimal Design of Continuum Robots with Reachability Constraints

Hyunmin Cheong, Mehran Ebrahimi, Timothy Duggan

IEEE Robotics and Automation Letters 2021

While multi-joint continuum robots are highly dexterous and flexible, designing an optimal robot can be challenging due to its kinematics involving curvatures. Hence, the current work presents a computational method developed to find optimal designs of continuum robots given reachability constraints. First, we leverage both forward and inverse kinematic computations to perform reachability analysis in an efficient yet accurate manner. While implementing inverse kinematics, we also integrate torque minimization at joints such that robot configurations with the minimum actuator torque required to reach a given workspace could be found. Lastly, we apply an estimation of distribution algorithm (EDA) to find optimal robot dimensions while considering reachability, where the objective function could be the total length of the robot or the actuator torque required to operate the robot. Through three application problems, we show that the EDA is superior to a genetic algorithm (GA) in finding better solutions within a given number of iterations, as the objective values of the best solutions found by the EDA are 4-15% lower than those found by the GA.