Sciweavers

Share
IROS
2009
IEEE

Using eigenposes for lossless periodic human motion imitation

8 years 12 months ago
Using eigenposes for lossless periodic human motion imitation
— Programming a humanoid robot to perform an action that takes the robot’s complex dynamics into account is a challenging problem. Traditional approaches typically require highly accurate prior knowledge of the robot’s dynamics and environment in order to devise complex control algorithms for generating a stable dynamic motion. Training using human motion capture is an intuitive and flexible approach to programming a robot but directly applying motion capture data to a robot usually results in dynamically unstable motion. Optimization using high-dimensional motion capture data in the humanoid full-body joint-space is also typically intractable. In previous work, we proposed an approach that uses dimensionality reduction to achieve tractable imitation-based learning in humanoids without the need for a physics-based dynamics model. This work was based on a 3-D “eigenpose” representation. However, for some motion patterns, using only three dimensions for eigenposes is insuffic...
Rawichote Chalodhorn, Rajesh P. N. Rao
Added 24 May 2010
Updated 24 May 2010
Type Conference
Year 2009
Where IROS
Authors Rawichote Chalodhorn, Rajesh P. N. Rao
Comments (0)
books