Reorientation of A Bio-Cat Falling Legged Robot Driven by Pneumatic Muscles with Energy Optimization

Nowadays, robots are facing unstructured environments with non-planar surfaces and high complexity during their operations. Cats can autonomously flip to adjust their orientation when falling, showing strong adaptability to complex environments. However, existing bio-cat robots still have shortcomings in joint drive forms and control system design. Currently, most robots are driven by motors, and the rigid body cannot provide cushioning when landing, which easily leads to motor damage. As such, a bio-cat falling-legged robot driven by pneumatic muscles(BCFLRDPM) is proposed, which uses series and parallel pneumatic muscle joints to form a flexible spine structure. In this paper, a complete dynamic mathematical model of the BCFLRDPM is established and its reorientation method is proposed, which employs modified particle swarm optimization (PSO) algorithm and cubic spline function trajectory fitting for minimizing energy consumption during free falling. The simulation results show that the reorientation with energy optimization for the BCFLRDPM can be realized with cooperative regulation of the pneumatic muscles.