# The Sense of Agency in Assistive Robotics Using Shared Autonomy

arXiv: https://arxiv.org/abs/2501.07462 · HTML: https://mlsanity.com/paper/2501.07462/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jan 2025.

## Built on by (most cited first, 8 of 8)

- [Casper: Inferring Diverse Intents for Assistive Teleoperation with Vision Language Models](https://mlsanity.com/paper/2506.14727/) (2025)
- [QuickLAP: Quick Language-Action Preference Learning for Semi-Autonomous Agents](https://mlsanity.com/paper/2511.17855/) (2025)
- [End-to-end Optimization of Belief and Policy Learning in Shared Autonomy Paradigms](https://mlsanity.com/paper/2601.23285/) (2026)
- [Improving through Interaction: Searching Behavioral Representation Spaces with CMA-ES-IG](https://mlsanity.com/paper/2603.09011/) (2026)
- [SAATT Nav: a Socially Aware Autonomous Transparent Transportation Navigation Framework for Wheelchairs](https://mlsanity.com/paper/2603.13698/) (2026)
- [HITL-D: Human In The Loop Diffusion Assisted Shared Control](https://mlsanity.com/paper/2605.21460/) (2026)
- [Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interaction](https://mlsanity.com/paper/2607.06344/) (2026)
- [BlenDAgger: Blended Shared Control for Interactive Imitation Learning](https://mlsanity.com/paper/2609.37599/) (2026)

## Abstract (arXiv)

Sense of agency is one factor that influences people's preferences for robot assistance and a phenomenon from cognitive science that represents the experience of control over one's environment. However, in assistive robotics literature, we often see paradigms that optimize measures like task success and cognitive load, rather than sense of agency. In fact, prior work has found that participants sometimes express a preference for paradigms, such as direct teleoperation, which do not perform well with those other metrics but give more control to the user. In this work, we focus on a subset of assistance paradigms for manipulation called shared autonomy in which the system combines control signals from the user and the automated control. We run a study to evaluate sense of agency and show that higher robot autonomy during assistance leads to improved task performance but a decreased sense of agency, indicating a potential trade-off between task performance and sense of agency. From our findings, we discuss the relation between sense of agency and optimality, and we consider a proxy metric for a component of sense of agency which might enable us to build systems that monitor and maintain sense of agency in real time.