Description: 

This is the video for "Efficient Motion Planning of Highly Articulated 
Chains using Physics-based Sampling," by Russell Gayle, Avneesh Sud, Stephane Redon, Ming C. Lin, and Dinesh Manocha. 

The video highlights various aspects of our work. The first segment shows results from our planning algorithm on a simple environment. An articulated robot with 300 degrees of freedom (DOF) must navigate through a sequence of walls with small holes. On the top, the fully articulated solution is presented. On the bottom, a solution using our adaptive dimensionality reduction method is shown for comparison. While the motion between the two is very similar, the reduced version is approximately 3 times faster. 

The second segment shows the results in a more difficult environment. A snake-like 'inspection' robot with 2000 DOF looks for leaks in industrial piping. Our adaptive forward dynamics algorithm only simulates 250 joints in the body, providing improvements in performance. 

Player Information: 

This video is in Quicktime mp4 format, and should be viewable with QuickTime Player version 7.1 or VLC media player version 0.8.6. It may work with earlier versions of these packages as well, but has not been tested. 

Contact Information: 

If you have any questions or are having trouble viewing the video, please contact Russell Gayle at rgayle@cs.unc.edu. 

Attachment filename: 1760_VI.mp4 (4937534 Bytes)