Abstract
AbstractThe effect of center of mass (CoM) trajectory on stable walking of biped robot was studied in this study. The method of predictive control by controlling CoM trajectory to generate stable walking patterns was discussed, which simulated the principle of adjusting center of gravity in advance during human walking to adapt to the change of road conditions. As for uncertainty of robot modeling and the influence of environment, adding variable zero moment point for variable predictive control system can achieve self-adaptive adjustment of CoM trajectory to generate stable walking patterns. The simulation experiment results indicated that walking stability of biped robot was sensitive to the change of CoM trajectory. As long as CoM trajectory was adjusted well, stable walking of biped robot can be controlled even in the presence of disturbances. It is proved that the method of predictive control by controlling CoM motion to generate stable walking pattern is consistent with reality.
Highlights
Biped robot walking based on the zero moment point (ZMP) has been widely applied and achieved remarkable achievements [1,2,3,4,5]
We demonstrated the method of stable walking based on predictive control of center of mass (CoM) trajectory, and walking pattern generation system can simulate self-adaptive adjusting strategy for center of gravity (CoG) during human walking
Predictive control can generate stable walking pattern by controlling the CoM motion, which is consistent with the real-time slight adjustment of CoG trajectory during human walking to adapt the change of road condition to achieve stable walking
Summary
Biped robot walking based on the zero moment point (ZMP) has been widely applied and achieved remarkable achievements [1,2,3,4,5]. The principle of controlling CoM motion to generate stable walking pattern is consistent with the requirement of adjusting CoG during human walking. Predictive control is to use future target ZMP information, which is consistent with the principle that human walking uses future road information to achieve precise control of CoM motion. [20], predictive control was first applied to biped robot research, and the theory of walking pattern generation based on predictive control was proposed. Predictive control based on CoM trajectory adjustment is consistent with the principle of human walking control. As human walking adjusted their CoG in advance, the predictive controller was designed to adjust CoM motion of robots. According to the discussion of predictive controller parameters in these studies [24,25], the following robot structure parameters and predictive controller parameters are applied to calculate and test
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