Constrained Model Predictive Control for a Hexapod Robot Walking on Irregular Terrain

It is usually a common task that walking on irregular terrain for a hexapod robot. This paper treats the problem of control of a hexapod robot that has been developed in a collaborative project of the Departments of Mechanical Engineering and Automation at Shanghai Jiao Tong University. We derive the hexapod robot’s kinematics and dynamics models, which are non-periodic, nonlinear, hybrid and open-loop unstable. In order to solve this challenge, we compute a transverse linearization about the desired motion which is a linear impulsive system. The real environment, where the robot performs tasks, are usually unstructured and dynamic, it is always difficult to know the size of obstacles the robot strikes on. In order to reduce its reliance on terrain information for locomotion control to the minimum, taking account of physical constraints, we propose a constrained model predictive controller for stabilization of non-periodic trajectories of the hexapod robot walking over irregular terrain. We prove the stability of the proposed controller theoretically. In the end we perform several simulations and experiments to verify the effectiveness of the control algorithm we proposed.