Back to Search
Start Over
Generating human-like soccer primitives from human data
- Source :
-
Robotics & Autonomous Systems . Jul2009, Vol. 57 Issue 8, p860-869. 10p. - Publication Year :
- 2009
-
Abstract
- Abstract: Recently, interest in analysis and generation of human and human-like motion has increased in various areas. In robotics, in order to operate a humanoid robot, it is necessary to generate motions that have strictly dynamic consistency. Furthermore, human-like motion for robots will bring advantages such as energy optimization. This paper presents a mechanism to generate two human-like motions, walking and kicking, for a biped robot using a simple model based on observation and analysis of human motion. Our ultimate goal is to establish a design principle of a controller in order to achieve natural human-like motions. The approach presented here rests on the principle that in most biological motor learning scenarios some form of optimization with respect to a physical criterion is taking place. In a similar way, the equations of motion for the humanoid robot systems are formulated in such a way that the resulting optimization problems can be solved reliably and efficiently. The simulation results show that faster and more accurate searching can be achieved to generate an efficient human-like gait. Comparison is made with methods that do not include observation of human gait. The gait has been successfully used to control Robo-Erectus, a soccer-playing humanoid robot, which is one of the foremost leading soccer-playing humanoid robots in the RoboCup Humanoid League. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 09218890
- Volume :
- 57
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- Robotics & Autonomous Systems
- Publication Type :
- Academic Journal
- Accession number :
- 41242567
- Full Text :
- https://doi.org/10.1016/j.robot.2009.03.005