Gait optimization of biped robots based on human motion analysis

This paper proposes a dynamically stable and optimal trajectory generation method for biped robots to walk up and down stairs, based on human motion analysis, since a human walks efficiently without high energy consumption, and the energy-efficient locomotion pattern results in a more natural walkin...

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Veröffentlicht in:Robotics and autonomous systems Jg. 62; H. 2; S. 229 - 240
Hauptverfasser: Lim, In-sik, Kwon, Ohung, Park, Jong Hyeon
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.02.2014
Schlagworte:
Biped robot
Gait
Genetic algorithms
Human
Human motion analysis
Locomotion pattern
Mathematical analysis
Mathematical models
Optimization
Robots
Staircase
Trajectories
Walking
Biped robot
Human motion analysis
Locomotion pattern
Optimization
Staircase
Genetic algorithms
ISSN:0921-8890, 1872-793X
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Zusammenfassung:This paper proposes a dynamically stable and optimal trajectory generation method for biped robots to walk up and down stairs, based on human motion analysis, since a human walks efficiently without high energy consumption, and the energy-efficient locomotion pattern results in a more natural walking pattern. Seven important elements of the human gait on stairs are identified in the analysis of the motion data captured from subjects. Those factors enable us to generate trajectories of biped robots similar to that of human beings walking up-and-down stairs. The dynamics of the robot and human are different in weight distribution, degree of freedom and so on. A real-coded genetic algorithm as an optimization tool is used to produce the optimized gait for the robot and to improve the energy autonomy and stability. Various computer simulations were performed based on a 12-DOF biped robot model with which many of the essential characteristics of the human walking motion on stairs can be captured. The proposed method exhibits its efficiency in quickly finding an optimal trajectory, which is due to not only the nature of genetic algorithms but also a small number of design variables employed. Thus, this makes it possible to generate various locomotion trajectories of biped robots simply by appropriately changing some of the boundary conditions.
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ISSN:0921-8890
1872-793X
DOI:10.1016/j.robot.2013.08.014