In this paper, using minimum energy function as an optimization tool, a stable trajectory for a humanoid robot to run is achieved with the genetic algorithm. Compared with other methods, it can reduce consumed energy ...
详细信息
ISBN:
(纸本)0780384032
In this paper, using minimum energy function as an optimization tool, a stable trajectory for a humanoid robot to run is achieved with the genetic algorithm. Compared with other methods, it can reduce consumed energy during the whole process. The proposed method is adaptive to various step lengths and step times for running and could be applied in other missions, such as walking, overcoming obstacles. The system stability is improved by controlling shoulders and elbows to compensate the errors. The performance of the proposed method is validated by simulation of a 28 DOF humanoid robot model with ADAMS.
Using minimum energy function as an optimization tool, a stable trajectory for a humanoid robot to run is achieved with the genetic algorithm. Compared with other methods, it can reduce consumed energy during the whol...
详细信息
ISBN:
(纸本)0780384032
Using minimum energy function as an optimization tool, a stable trajectory for a humanoid robot to run is achieved with the genetic algorithm. Compared with other methods, it can reduce consumed energy during the whole process. The proposed method is adaptive to various step lengths and step times for running and could be applied in other missions, such as walking, overcoming obstacles. The system stability is improved by controlling shoulders and elbows to compensate the errors. The performance of the proposed method is validated by simulation of a 28 DOF humanoid robot model with ADAMS.
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