# Operation and Imitation under Safety-Aware Shared Control

## TL;DR

This paper presents a safety-aware shared control method that enhances human control, aids in training, and enables imitation learning to replicate behaviors without prior task knowledge.

## Contribution

The authors introduce a shared control algorithm that enforces safety constraints and can be combined with imitation learning to generate autonomous behaviors without task-specific knowledge.

## Key findings

- Significantly improves user success in executing novel behaviors
- Enhances human understanding and control skills
- Enables autonomous reproduction of demonstrated behaviors

## Abstract

We describe a shared control methodology that can, without knowledge of the task, be used to improve a human's control of a dynamic system, be used as a training mechanism, and be used in conjunction with Imitation Learning to generate autonomous policies that recreate novel behaviors. Our algorithm introduces autonomy that assists the human partner by enforcing safety and stability constraints. The autonomous agent has no a priori knowledge of the desired task and therefore only adds control information when there is concern for the safety of the system. We evaluate the efficacy of our approach with a human subjects study consisting of 20 participants. We find that our shared control algorithm significantly improves the rate at which users are able to successfully execute novel behaviors. Experimental results suggest that the benefits of our safety-aware shared control algorithm also extend to the human partner's understanding of the system and their control skill. Finally, we demonstrate how a combination of our safety-aware shared control algorithm and Imitation Learning can be used to autonomously recreate the demonstrated behaviors.