A new task-consistent overturn prevention algorithm for redundant mobile modular manipulators

This paper presents a new algorithm for automatic overturn prevention and path following control of redundant nonholonomic mobile modular manipulators. According to modular robot concept, a new dynamic modeling method is proposed in consideration of interactive motions, nonholonomic constraints and self-motions. Then, an online self-motion planner (SMP) and a robust adaptive neural-fuzzy controller (RANFC) are devised; the former is used to generate desired self-motions in a real-time manner, while the latter is used to prevent the robot from overturning and to control the end-effector to follow a desired spacial trajectory at the same time. The proposed algorithm does not need exact apriori knowledge of dynamic parameters and can suppress bounded external disturbance effectively. Simulation results for a real robot demonstrate that the proposed algorithm is effective.