Giving Sense to Inputs: Toward an Accessible Control Framework for Shared Autonomy

TL;DR

This paper introduces a dynamic input mapping framework for shared autonomy in assistive robotics, linking joystick inputs to complex robot motions, and demonstrates its effectiveness through user studies with both able-bodied participants and wheelchair users.

Contribution

The paper presents a novel control framework that simplifies 2D joystick inputs into 6D robot motions using control frames along trajectories, enhancing usability and reducing workload.

Findings

Reduced user workload in control tasks

Improved usability over baseline mappings

Feasibility demonstrated with wheelchair users

Abstract

While shared autonomy offers significant potential for assistive robotics, key questions remain about how to effectively map 2D control inputs to 6D robot motions. An intuitive framework should allow users to input commands effortlessly, with the robot responding as expected, without users needing to anticipate the impact of their inputs. In this article, we propose a dynamic input mapping framework that links joystick movements to motions on control frames defined along a trajectory encoded with canal surfaces. We evaluate our method in a user study with 20 participants, demonstrating that our input mapping framework reduces the workload and improves usability compared to a baseline mapping with similar motion encoding. To prepare for deployment in assistive scenarios, we built on the development from the accessible gaming community to select an accessible control interface. We then tested the system in an exploratory study, where three wheelchair users controlled the robot for both daily living activities and a creative painting task, demonstrating its feasibility for users closer to our target population.