Active articulation model estimation through interactive perception

Karol Hausman, Scott Niekum, Sarah Osentoski, Gaurav S. Sukhatme
2015 2015 IEEE International Conference on Robotics and Automation (ICRA)  
We introduce a particle filter-based approach to representing and actively reducing uncertainty over articulated motion models. The presented method provides a probabilistic model that integrates visual observations with feedback from manipulation actions to best characterize a distribution of possible articulation models. We evaluate several action selection methods to efficiently reduce the uncertainty about the articulation model. The full system is experimentally evaluated using a PR2
more » ... manipulator. Our experiments demonstrate that the proposed system allows for intelligent reasoning about sparse, noisy data in a number of common manipulation scenarios.
doi:10.1109/icra.2015.7139655 dblp:conf/icra/HausmanNOS15 fatcat:7rfvc3dfobgdxi4kxqmj7gsiim