# PrioriTouch: Adapting to User Contact Preferences for Whole-Arm Physical Human-Robot Interaction

arXiv: https://arxiv.org/abs/2509.18447 · HTML: https://mlsanity.com/paper/2509.18447/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 37 references that are in the map.
- First posted on arXiv 22 Sep 2025.

## Builds on (most cited first, 16 of 16)

- [A Contextual Bandit Bake-off](https://mlsanity.com/paper/1802.04064/) (2018)
- [Physical Interaction as Communication: Learning Robot Objectives Online from Human Corrections](https://mlsanity.com/paper/2107.02349/) (2021)
- [Touch-GS: Visual-Tactile Supervised 3D Gaussian Splatting](https://mlsanity.com/paper/2403.09875/) (2024)
- [Including Uncertainty when Learning from Human Corrections](https://mlsanity.com/paper/1806.02454/) (2018)
- [Adaptive Robot-Assisted Feeding: An Online Learning Framework for Acquiring Previously Unseen Food Items](https://mlsanity.com/paper/1908.07088/) (2019)
- [RCareWorld: A Human-centric Simulation World for Caregiving Robots](https://mlsanity.com/paper/2210.10821/) (2022)
- [HumanRig: Learning Automatic Rigging for Humanoid Character in a Large Scale Dataset](https://mlsanity.com/paper/2412.02317/) (2024)
- [CushSense: Soft, Stretchable, and Comfortable Tactile-Sensing Skin for Physical Human-Robot Interaction](https://mlsanity.com/paper/2405.03155/) (2024)
- [Learning Human Preferences Over Robot Behavior as Soft Planning Constraints](https://mlsanity.com/paper/2403.19795/) (2024)
- [The Six Hug Commandments: Design and Evaluation of a Human-Sized Hugging Robot with Visual and Haptic Perception](https://mlsanity.com/paper/2101.07679/) (2021)
- [RABBIT: A Robot-Assisted Bed Bathing System with Multimodal Perception and Integrated Compliance](https://mlsanity.com/paper/2401.15159/) (2024)
- [Manipulation in Clutter with Whole-Arm Tactile Sensing](https://mlsanity.com/paper/1304.6146/) (2013)
- [RobotSweater: Scalable, Generalizable, and Customizable Machine-Knitted Tactile Skins for Robots](https://mlsanity.com/paper/2303.02858/) (2023)
- [Punyo-1: Soft tactile-sensing upper-body robot for large object manipulation and physical human interaction](https://mlsanity.com/paper/2111.09354/) (2021)
- [StROL: Stabilized and Robust Online Learning from Humans](https://mlsanity.com/paper/2308.09863/) (2023)
- [CART-MPC: Coordinating Assistive Devices for Robot-Assisted Transferring with Multi-Agent Model Predictive Control](https://mlsanity.com/paper/2501.11149/) (2025)

## Abstract (arXiv)

Physical human-robot interaction (pHRI) requires robots to adapt to individual contact preferences, such as where and how much force is applied. Identifying preferences is difficult for a single contact; with whole-arm interaction involving multiple simultaneous contacts between the robot and human, the challenge is greater because different body parts can impose incompatible force requirements. In caregiving tasks, where contact is frequent and varied, such conflicts are unavoidable. With multiple preferences across multiple contacts, no single solution can satisfy all objectives--trade-offs are inherent, making prioritization essential. We present PrioriTouch, a framework for ranking and executing control objectives across multiple contacts. PrioriTouch can prioritize from a general collection of controllers, making it applicable not only to caregiving scenarios such as bed bathing and dressing but also to broader multi-contact settings. Our method combines a novel learning-to-rank approach with hierarchical operational space control, leveraging simulation-in-the-loop rollouts for data-efficient and safe exploration. We conduct a user study on physical assistance preferences, derive personalized comfort thresholds, and incorporate them into PrioriTouch. We evaluate PrioriTouch through extensive simulation and real-world experiments, demonstrating its ability to adapt to user contact preferences, maintain task performance, and enhance safety and comfort. Website: https://emprise.cs.cornell.edu/prioritouch.