Abstract
Biped robots are similar to human beings and have broad application prospects in the fields of family service, disaster rescue and military affairs. However, simplified models and fixed center of mass (COM) used in previous research ignore the large-scale stability control ability implied by whole-body motion. The present paper proposed a two-level controller based on a simplified model and whole-body dynamics. In high level, a model predictive control (MPC) controller is implemented to improve zero moment point (ZMP) control performance. In low level, a quadratic programming optimization method is adopted to realize trajectory tracking and stabilization with friction and joint constraints. The simulation shows that a 12-degree-of-freedom force-controlled biped robot model, adopting the method proposed in this paper, can recover from a 40 Nm disturbance when walking at 1.44 km/h without adjusting the foot placement, and can walk on an unknown 4 cm high stairs and a rotating slope with a maximum inclination of 10°. The method is also adopted to realize fast walking up to 6 km/h.
Highlights
Humanoid robots imitate the form of human biped walking with the aim to move in unstructured complex environments and overcome external disturbances [1,2]
Six degrees of freedom free movement joints were added between the body and the world, and their states were measured as inertial measurement unit (IMU) sensor output
We used a two-level controller, of model predictive control (MPC) controller and whole-body controller, to recovery, uneven ground walking and fast walking compared to a simplified model
Summary
Humanoid robots imitate the form of human biped walking with the aim to move in unstructured complex environments and overcome external disturbances [1,2]. A good performance for a walking robot can be defined as moving from a starting to a goal point without falling down within disturbance, which is usually caused by external force disturbance, uneven ground and unmodeled dynamics in high dynamic motion. In this sense, the main objective of the control in a walking robot is to guarantee zero moment point (ZMP). Generating fast and stable walking under disturbance for humanoid robots is a multidisciplinary and complex subject, due to the naturally unstable dynamics of these types of robots. To reduce the difficulty of robot stability control, the overall structure of the walking system in preview works is usually decoupled into four hierarchy levels, which are footstep planner, reference generators, disturbance recovery and low-level controller [4]
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