# Going In Blind: Object Motion Classification using Distributed Tactile Sensing for Safe Reaching in Clutter

arXiv: https://arxiv.org/abs/2210.00137 · HTML: https://mlsanity.com/paper/2210.00137/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Sep 2022.

## Built on by (most cited first, 2 of 2)

- [Universal Manipulation Exoskeleton: Learning Compliant Whole-body Policies with Real-time Torque Feedback](https://mlsanity.com/paper/2606.14218/) (2026)
- [Gentle Object Retraction in Dense Clutter Using Multimodal Force Sensing and Imitation Learning](https://mlsanity.com/paper/2508.19476/) (2025)

## Abstract (arXiv)

Robotic manipulators navigating cluttered shelves or cabinets may find it challenging to avoid contact with obstacles. Indeed, rearranging obstacles may be necessary to access a target. Rather than planning explicit motions that place obstacles into a desired pose, we suggest allowing incidental contacts to rearrange obstacles while monitoring contacts for safety. Bypassing object identification, we present a method for categorizing object motions from tactile data collected from incidental contacts with a capacitive tactile skin on an Allegro Hand. We formalize tactile cues associated with categories of object motion, demonstrating that they can determine with >90% accuracy whether an object is movable and whether a contact is causing the object to slide stably (safe contact) or tip (unsafe).