# Spatially anchored Tactile Awareness for Robust Dexterous Manipulation

arXiv: https://arxiv.org/abs/2510.14647 · HTML: https://mlsanity.com/paper/2510.14647/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Oct 2025.

## Built on by (most cited first, 7 of 7)

- [T-Rex: Tactile-Reactive Dexterous Manipulation](https://mlsanity.com/paper/2606.17055/) (2026)
- [Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning](https://mlsanity.com/paper/2606.11767/) (2026)
- [ADEPT: Accelerating Dexterity via Pre-Training and Post-Training using Reinforcement Learning](https://mlsanity.com/paper/2608.19182/) (2026)
- [Tac2Pix: Image-Space Visuo-Tactile Fusion for Dexterous Manipulation](https://mlsanity.com/paper/2606.08765/) (2026)
- [GeoTLM: Geometry-aware Tactile-Language Models for Contact Motion Orientation Reasoning of Dynamic Objects](https://mlsanity.com/paper/2606.15909/) (2026)
- [DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imagination](https://mlsanity.com/paper/2609.09119/) (2026)
- [DexTacWAM: A Visuo-Tactile World-Action Model for Dexterous Manipulation](https://mlsanity.com/paper/2609.24976/) (2026)

## Abstract (arXiv)

Dexterous manipulation requires precise geometric reasoning, yet existing visuo-tactile learning methods struggle with sub-millimeter precision tasks that are routine for traditional model-based approaches. We identify a key limitation: while tactile sensors provide rich contact information, current learning frameworks fail to effectively leverage both the perceptual richness of tactile signals and their spatial relationship with hand kinematics. We believe an ideal tactile representation should explicitly ground contact measurements in a stable reference frame while preserving detailed sensory information, enabling policies to not only detect contact occurrence but also precisely infer object geometry in the hand's coordinate system. We introduce SaTA (Spatially-anchored Tactile Awareness for dexterous manipulation), an end-to-end policy framework that explicitly anchors tactile features to the hand's kinematic frame through forward kinematics, enabling accurate geometric reasoning without requiring object models or explicit pose estimation. Our key insight is that spatially grounded tactile representations allow policies to not only detect contact occurrence but also precisely infer object geometry in the hand's coordinate system. We validate SaTA on challenging dexterous manipulation tasks, including bimanual USB-C mating in free space, a task demanding sub-millimeter alignment precision, as well as light bulb installation requiring precise thread engagement and rotational control, and card sliding that demands delicate force modulation and angular precision. These tasks represent significant challenges for learning-based methods due to their stringent precision requirements. Across multiple benchmarks, SaTA significantly outperforms strong visuo-tactile baselines, improving success rates by up to 30 percentage while reducing task completion times by 27 percentage.