The motion planning for obstacle negotiation by humanoid robot BHR-2 through stepping over or stepping on/off the wide and flat obstacle at known locations is presented. In the trajectory generation method, first the ...The motion planning for obstacle negotiation by humanoid robot BHR-2 through stepping over or stepping on/off the wide and flat obstacle at known locations is presented. In the trajectory generation method, first the constraints of the foot motion parameters which include obstacle dimensions and the distance of obstacle from the humanoid robot is formulated. By varying the values of the constraint parameters, different types of foot motion for different obstacles can be produced. In this method, first the foot trajectory is generated, and then the waist trajectory is computed by using cubic spline interpolation without first calculating the zero moment point （ZMP） trajectory . The dynamic stability during the execution of stepping over and stepping on/off trajectories are ensured by incorporating the ZMP criterion. The effectiveness of the proposed method is confirmed by simulations and experiments on humanoid robot BHR-2.展开更多
基金Sponsored by the National"863"Program Project (1020021300704)
文摘The motion planning for obstacle negotiation by humanoid robot BHR-2 through stepping over or stepping on/off the wide and flat obstacle at known locations is presented. In the trajectory generation method, first the constraints of the foot motion parameters which include obstacle dimensions and the distance of obstacle from the humanoid robot is formulated. By varying the values of the constraint parameters, different types of foot motion for different obstacles can be produced. In this method, first the foot trajectory is generated, and then the waist trajectory is computed by using cubic spline interpolation without first calculating the zero moment point （ZMP） trajectory . The dynamic stability during the execution of stepping over and stepping on/off trajectories are ensured by incorporating the ZMP criterion. The effectiveness of the proposed method is confirmed by simulations and experiments on humanoid robot BHR-2.
