# Fault-tolerant Control of Robot Manipulators with Sensory Faults using Unbiased Active Inference

arXiv: https://arxiv.org/abs/2104.01817 · HTML: https://mlsanity.com/paper/2104.01817/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Apr 2021.

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

- [Active Inference in Robotics and Artificial Agents: Survey and Challenges](https://mlsanity.com/paper/2112.01871/) (2021)
- [Adaptation through prediction: multisensory active inference torque control](https://mlsanity.com/paper/2112.06752/) (2021)
- [Review on Fault Diagnosis and Fault-Tolerant Control Scheme for Robotic Manipulators: Recent Advances in AI, Machine Learning, and Digital Twin](https://mlsanity.com/paper/2402.02980/) (2024)
- [Active Inference for an Intelligent Agent in Autonomous Reconnaissance Missions](https://mlsanity.com/paper/2510.17450/) (2025)
- [Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness Levels](https://mlsanity.com/paper/2607.26121/) (2026)

## Abstract (arXiv)

This work presents a novel fault-tolerant control scheme based on active inference. Specifically, a new formulation of active inference which, unlike previous solutions, provides unbiased state estimation and simplifies the definition of probabilistically robust thresholds for fault-tolerant control of robotic systems using the free-energy. The proposed solution makes use of the sensory prediction errors in the free-energy for the generation of residuals and thresholds for fault detection and isolation of sensory faults, and it does not require additional controllers for fault recovery. Results validating the benefits in a simulated 2-DOF manipulator are presented, and future directions to improve the current fault recovery approach are discussed.