# Thermal Recovery of Multi-Limbed Robots with Electric Actuators

arXiv: https://arxiv.org/abs/1902.00187 · HTML: https://mlsanity.com/paper/1902.00187/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Feb 2019.

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

- [Deep Learning for Model-Free Prediction of Thermal States of Robot Joint Motors](https://mlsanity.com/paper/2509.12739/) (2025)
- [Deep Generative and Discriminative Digital Twin endowed with Variational Autoencoder for Unsupervised Predictive Thermal Condition Monitoring of Physical Robots in Industry 6.0 and Society 6.0](https://mlsanity.com/paper/2509.12740/) (2025)

## Abstract (arXiv)

The problem of finding thermally minimizing configurations of a humanoid robot to recover its actuators from unsafe thermal states is addressed. A first-order, data-driven, effort-based, thermal model of the robot's actuators is devised, which is used to predict future thermal states. Given this predictive capability, a map between configurations and future temperatures is formulated to find what configurations, subject to valid contact constraints, can be taken now to minimize future thermal states. Effectively, this approach is a realization of a contact-constrained thermal inverse-kinematics (IK) process. Experimental validation of the proposed approach is performed on the NASA Valkyrie robot hardware.