Generation and control of locomotion patterns for biped robots by using central pattern generators

Julián Efrén Cristiano Rodríguez, Domènec Puig Valls, Miguel Angel García García


This paper presents an efficient closed-loop locomotion control system for biped robots that operates in the joint space. The robot’s joints are directly driven through control signals generated by a central pattern generator (CPG) network. A genetic algorithm is applied in order to find out an optimal combination of internal parameters of the CPG given a desired walking speed in straight line. Feedback signals generated by the robot’s inertial and force sensors are directly fed into the CPG in order to automatically adjust the locomotion pattern over uneven terrain and to deal with external perturbations in real time. Omnidirectional motion is achieved by controlling the pelvis motion. The performance of the proposed control system has been assessed through simulation experiments on a NAO humanoid robot.


Adaptive control; Biologically inspired control; Central pattern generators; CPGs; Matsuoka’s oscillator


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