Simulation of Improved Bipedal Running Based on Swing Leg Control and Whole-body Dynamics

The realization of running motion can greatly improve the athletic performance of the legged mobile robot. The biologically inspired deadbeat (BID) controller realizes robust bipedal running, allows versatile running patterns and is realtime capable. However, the lack of precise position adjustment strategy of swing leg leads to large center of mass (CoM) tracking error and slow convergence to steady state when perturbed. This paper proposed a simple event-based controller of swing leg position on the basis of the BID controller, using feedback of the system state at the lift off moment. And a linear quadratic regulator (LQR) is used to adjust the feedback gains. The controllers are then embeded into a whole-body control framework, which unifies the task space objectives and the physical constraints of dynamics, contact, ZMP and friction. Meanwhile, the physical limitations of the real robot such as joint torque amplitude and foot size are guaranteed. The proposed control framework was implemented on a torque-controlled bipedal robot and realize steady running in a simulated environment. And the swing leg control is proved under push recovery which decreases the CoM tracking error from 0.076m to 0.045m and recovery time from 2.34s to 1.22s.