Fault-tolerant joint state feedback adaptive control for snake robots that move through random pole environments

In unstructured terrain, snakes can move more efficiently by actively pushing and avoiding obstacles, a capability believed to be realized through a decentralized mechanism. Moreover, considering harsh and unpredictable rescue environments where snake robots are expected to be deployed, such as post-earthquake scenarios, some joint sensors are prone to failure. We propose a decentralized adaptation mechanism for snake robots to navigate through random pole environments. This mechanism integrates Fault-Tolerant Joint State Feedback Adaptive Control (FT-JSFAC) with Extended Curvature Derivatives control (ECD) and Angular Damping control (AD), leveraging the FT-JSFAC method to maintain operational robustness even when some joint sensors fail. To meet critical goals of adaptability, we utilize real-time angle and electrical current data from the robot's internal servo motors. Using this data, FT-JSFAC determines whether an obstacle is beneficial or detrimental to propulsion and then allows for decentralized torque adjustment to adapt to the environment. FT-JSFAC also employs historical data from functioning joints to compensate for erroneous sensor data, ensuring operational robustness even with joint sensor failure. Simulation experiments demonstrate that the proposed mechanism effectively adapts to environmental obstacles and maintains adaptability when one or two joint sensors fail.