  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.
