In this paper an experiment of human locomotion was carried out using a motion capture system to extract the human gait features. The modifiable key gait parameters affecting the dominant performance of biped robot walking were obtained from the extracted human gait features. Based on the modifiable key gait parameters and the Allowable Zero Moment Point (ZMP) Variation Region (AZR), we proposed an effective Bio-inspired Gait Planning (BGP) and control scheme for biped robot towards a given travel distance D. First, we construct an on-line Bio-inspired Gait Synthesis algorithm (BGSN) to generate a complete walking gait motion using the modifiable key gait parameters. Second, a Bio-inspired Gait Parameters Optimization algorithm (BGPO) is established to minimize the energy consumption of all actuators and guarantee biped robot walking with certain walking stability margin. Third, the necessary controllers for biped robot were introduced in briefly. Simulation and experiment results demonstrated the effectiveness of the proposed method, and the gait control system was implemented on DRC-XT humanoid robot.

 

Keywords

motion capture; Allowable Zero Moment Point (ZMP) Variation Region (AZR); Bio-inspired Gait Planning (BGP); humanoid robot

 

Full text is available at http://www.sciencedirect.com/science/article/pii/S1672652916603001