# Bodily aware soft robots: integration of proprioceptive and exteroceptive sensors

arXiv: https://arxiv.org/abs/1710.05419 · HTML: https://mlsanity.com/paper/1710.05419/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Oct 2017.

## Built on by (most cited first, 5 of 5)

- [Visual-Tactile Sensing for Real-time Liquid Volume Estimation in Grasping](https://mlsanity.com/paper/2202.11503/) (2022)
- [Just aware enough: Evaluating awareness across artificial systems](https://mlsanity.com/paper/2601.14901/) (2026)
- [What AIs are not Learning (and Why)](https://mlsanity.com/paper/2404.04267/) (2024)
- [Towards Interpretable Visuo-Tactile Predictive Models for Soft Robot Interactions](https://mlsanity.com/paper/2407.12197/) (2024)
- [Grounding Bodily Awareness in Visual Representations for Efficient Policy Learning](https://mlsanity.com/paper/2505.18487/) (2025)

## Abstract (arXiv)

Being aware of our body has great importance in our everyday life. This is the reason why we know how to move in a dark room or to grasp a complex object. These skills are important for robots as well, however, robotic bodily awareness is still an unsolved problem. In this paper we present a novel method to implement bodily awareness in soft robots by the integration of exteroceptive and proprioceptive sensors. We use a combination of a stacked convolutional autoencoder and a recurrent neural network to map internal sensory signals to visual information. As a result, the simulated soft robot can learn to textitimagine its motion even when its visual sensor is not available.