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 wa...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 to- wards 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.展开更多
Based on the ZMP(zero moment point)trajectory and the walking data of human,a new method is proposed to improve the robot walking smoothness as well as to save energy.Firstly,a measurement system is designed to measur...Based on the ZMP(zero moment point)trajectory and the walking data of human,a new method is proposed to improve the robot walking smoothness as well as to save energy.Firstly,a measurement system is designed to measure the data of humans including the ZMP trajectory and the waist trajectory.Secondly,a new gait planning method which includes presetting the allowable ZMP region is proposed through analyzing human data.Thirdly,the new planning method is applied to the multi-link model based gait planning method.Finally,the feasibility of the proposed method is verified by simulation and experiments.展开更多
基金Acknowledgment This research has been supported by Project of Science and Technology Support Plan of Jiangsu province （Grant No. BE2012057） and Science and Technology Support Plan Key Projects of Jiangsu province （Grant No. BE2013003） and National Nature Science Foundation of China （Grant No. 51405469）.
文摘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 to- wards 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.
基金the National Natural Science Foundation of China(61320106012,61533004,61375103,61673069,61321002)the 863 Program of China(2015AA043202,2015AA042305)+2 种基金the Key Technologies R&D Program(2015BAF13B01,2015BAK35B01)the Beijing Municipal Science and Technology Project(D161100003016002)the"111"Project(B08043)
文摘Based on the ZMP(zero moment point)trajectory and the walking data of human,a new method is proposed to improve the robot walking smoothness as well as to save energy.Firstly,a measurement system is designed to measure the data of humans including the ZMP trajectory and the waist trajectory.Secondly,a new gait planning method which includes presetting the allowable ZMP region is proposed through analyzing human data.Thirdly,the new planning method is applied to the multi-link model based gait planning method.Finally,the feasibility of the proposed method is verified by simulation and experiments.
