Fault-Tolerant Control of a Mole Cricket-Inspired Quadruped Robot with Functional Arms under Single-Leg Loss

Loss of leg function in quadruped robots often leads to severe mobility degradation in complex environments. Inspired by the effective forelimb utilization of the oriental mole cricket, this paper proposes a cooperative compensation strategy that integrates morphological design, gait optimization, and reinforcement learning to address single-leg failure. A novel configuration of a sprawled-posture quadruped robot equipped with two functional arms is developed. Based on kinematic analysis and the longitudinal stability margin criterion, a dynamic gait adjustment method is derived. Two control frameworks—a Central Pattern Generator (CPG) model and a Deep Deterministic Policy Gradient (DDPG) reinforcement learning approach—are developed and evaluated. Simulation results demonstrate that the bio-inspired arm compensation effectively mitigates yaw motion during foreleg failure. For the more challenging hindleg failure, the reinforcement learning controller significantly outperforms CPG limiting yaw fluctuation to a narrow range of -0.11 to -0.09 rad. Physical experiments validate that the proposed strategy restores walking performance to over 85% of the normal performance. After reinforcement learning training, mobility is not only fully recovered but slightly surpasses normal performance, with yaw error approaching zero. This work demonstrates a "morphology–control" cooperative compensation paradigm, enhancing fault tolerance and robustness of legged robots in unstructured hazardous environments.