# Planning for Muscular and Peripersonal-Space Comfort during Human-Robot Forceful Collaboration

arXiv: https://arxiv.org/abs/1807.11323 · HTML: https://mlsanity.com/paper/1807.11323/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jul 2018.

## Built on by (most cited first, 4 of 4)

- [DULA: A Differentiable Ergonomics Model for Postural Optimization in Physical HRI](https://mlsanity.com/paper/2107.06875/) (2021)
- [Ergonomically Intelligent Physical Human-Robot Interaction: Postural Estimation, Assessment, and Optimization](https://mlsanity.com/paper/2108.05971/) (2021)
- [DULA and DEBA: Differentiable Ergonomic Risk Models for Postural Assessment and Optimization in Ergonomically Intelligent pHRI](https://mlsanity.com/paper/2205.03491/) (2022)
- [Occlusion-Robust Multi-Sensory Posture Estimation in Physical Human-Robot Interaction](https://mlsanity.com/paper/2208.06494/) (2022)

## Abstract (arXiv)

This paper presents a planning algorithm designed to improve cooperative robot behavior concerning human comfort during forceful human-robot physical interaction. Particularly, we are interested in planning for object grasping and positioning ensuring not only stability against the exerted human force but also empowering the robot with capabilities to address and improve human experience and comfort. Herein, comfort is addressed as both the muscular activation level required to exert the cooperative task, and the human spatial perception during the interaction, namely, the peripersonal space. By maximizing both comfort criteria, the robotic system can plan for the task (ensuring grasp stability) and for the human (improving human comfort). We believe this to be a key element to achieve intuitive and fluid human-robot interaction in real applications. Real HRI drilling and cutting experiments illustrated the efficiency of the proposed planner in improving overall comfort and HRI experience without compromising grasp stability.