Sampling-based trajectory imitation in constrained environments using Laplacian-RRT | IEEE Conference Publication | IEEE Xplore

Sampling-based trajectory imitation in constrained environments using Laplacian-RRT


Abstract:

This paper presents an incremental sampling-based approach for trajectory imitation in cluttered environments using the RRT* algorithm. Inspired by the discrete Laplace-B...Show More

Abstract:

This paper presents an incremental sampling-based approach for trajectory imitation in cluttered environments using the RRT* algorithm. Inspired by the discrete Laplace-Beltrami operator the underlying distance metric is based upon the difference from a reference trajectory through a quadratic distance term incorporating velocity and acceleration deviations along the trajectory. Mathematically-backed approximations in combination with a task-space bias make it possible to use standard nearest neighbor methods in task space when expanding the RRT*-tree. It is shown that metric-consistent biases considerably increase the convergence speed. The proposed approach is validated in simulations in a 2D environment and in experiments using a HRP-4 humanoid robot.
Date of Conference: 14-18 September 2014
Date Added to IEEE Xplore: 06 November 2014
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Conference Location: Chicago, IL, USA

References

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