Sari
Shared Autonomy across Repeated Interaction
Bibliographic Data
| ID | 22190675 |
|---|---|
| Authors | Ananth Jonnavittula (0000-0002-0711-2051, Virginia Tech), Shaunak A Mehta (0000-0002-3160-6879, Virginia Tech), Dylan P Losey (0000-0002-8787-5293, Virginia Tech) |
| Year | 2024 |
| Volume | 13 |
| Issue | 2 |
| Pages | 1-36 |
| Publication date | 2024-06-30 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ACM Transactions on Human-Robot Interaction (JOURNAL) |
| Journal identifiers | ISSN: 2573-9522 • E-ISSN: 2573-9522 |
| Publisher | Association for Computing Machinery (ACM) (PUBLISHER) |
| DOI | 10.1145/3651994 |
| OpenAlex | W4392590681 |
| Language | EN |
| Citations received | 1 |
| References cited | 36 |
Assistive robot arms try to help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy . Within shared autonomy, both the human and robot maintain control over the robot’s motion: as the robot becomes confident it understands what the human wants, it intervenes to automate the task. But how does the robot know these tasks in the first place? State-of-the-art approaches to shared autonomy often rely on prior knowledge. For instance, the robot may need to know the human’s potential goals beforehand. During long-term interaction these methods will inevitably break down—sooner or later the human will attempt to perform a task that the robot does not expect. Accordingly, in this article we formulate an alternate approach to shared autonomy that learns assistance from scratch. Our insight is that operators repeat important tasks on a daily basis (e.g., opening the fridge, making coffee). Instead of relying on prior knowledge, we therefore take advantage of these repeated interactions to learn assistive policies. We introduce SARI, an algorithm that recognizes the human’s task, replicates similar demonstrations, and returns control when unsure. We then combine learning with control to demonstrate that the error of our approach is uniformly ultimately bounded. We perform simulations to support this error bound, compare our approach to imitation learning baselines, and explore its capacity to assist for an increasing number of tasks. Finally, we conduct three user studies with industry-standard methods and shared autonomy baselines, including a pilot test with a disabled user. Our results indicate that learning shared autonomy across repeated interactions matches existing approaches for known tasks and outperforms baselines on new tasks. See videos of our user studies here: https://youtu.be/3vE4omSvLvc
Autonomy · Human–computer interaction · Human–robot interaction · Imitation · Robot · Computer Science · Engineering · Prosthetics and Rehabilitation Robotics · Psychology · Robot Manipulation and Learning · Social Psychology · Social Robot Interaction and HRI · Artificial Intelligence
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |