Dynamically adapt to uneven terrain walking control for humanoid robot

Dynamically adapt to uneven ground locomotion is a crucial ability for humanoid robots utilized in human environments. However, because of the effect of current pattern generation method, adapting to unknown rough ground is limited. Moreover, to maintain large support region by four-point contact during the landing phase is usually a key problem. In order to solve these problems, a landing phase control and online pattern generation in three dimensional environments is proposed. On the basis of robot-environment non-planar interactive modes, a method of landing control based on optimal support region is put forward to realize stable four-point contact by flexible foot, and a controller is employed to adapt to the changes of ground without using prior knowledge. Furthermore, an adaptable foothold planning is put forward to the online pattern generation considering walking speed, uneven terrain, and the effect of lateral movement to the locomotion stability. Finally, the effectiveness of landing control and online pattern generation is demonstrated by dynamic simulations and real robot walking experiments on outdoor uneven ground. The results indicate that the robot kept its balance even though the ground is unknown and irregular. The proposed methods lay a foundation for studies of humanoid robots performing tasks in complex environments.