Show Me What You Can Do: Capability Calibration on Reachable Workspace for Human-Robot Collaboration
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Abstract (arXiv)
Aligning humans' assessment of what a robot can do with its true capability is crucial for establishing a common ground between human and robot partners when they collaborate on a joint task. In this work, we propose an approach to calibrate humans' estimate of a robot's reachable workspace through a small number of demonstrations before collaboration. We develop a novel motion planning method, REMP, which jointly optimizes the physical cost and the expressiveness of robot motion to reveal the robot's reachability to a human observer. Our experiments with human participants demonstrate that a short calibration using REMP can effectively bridge the gap between what a non-expert user thinks a robot can reach and the ground truth. We show that this calibration procedure not only results in better user perception, but also promotes more efficient human-robot collaborations in a subsequent joint task.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 7 of its 44 references that are in the map. First posted on arXiv 6 Mar 2021.
Builds on
7 of 44 references.
References · 7
- 2018Establishing Appropriate Trust via Critical Statescited by 48
- 2019Reasoning about Hypothetical Agent Behaviours and their Parameterscited by 24
- 2017Game-Theoretic Modeling of Human Adaptation in Human-Robot Collaborationcited by 21
- 2018Expressing Robot Incapabilitycited by 13
- 2020Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaborationcited by 7
- 2017Communicating Robot Arm Motion Intent Through Mixed Reality Head-mounted Displayscited by 6
- 2019Robot Capability and Intention in Trust-based Decisions across Taskscited by 6
Built on by
Citing papers per year: 2024: 3; 2025: 1.
4 papers.
- 2025PhysVLM: Enabling Visual Language Models to Understand Robotic Physical Reachabilitycited by 18
- 2024GOMA: Proactive Embodied Cooperative Communication via Goal-Oriented Mental Alignmentcited by 16
- 2024On the Emergence of Symmetrical Realitycited by 8
- 2024Boltzmann State-Dependent Rationalitycited by 0
- 2025PhysVLM: Enabling Visual Language Models to Understand Robotic Physical Reachability11 Mar 2025
- 2024Boltzmann State-Dependent Rationality26 Apr 2024
- 2024GOMA: Proactive Embodied Cooperative Communication via Goal-Oriented Mental Alignment17 Mar 2024
- 2024On the Emergence of Symmetrical Reality26 Jan 2024