Authors: Jory Denny, Read Sandström, Nancy M. Amato

Venue: In Proc. Inter. Symp. on Robotics Research (ISRR 2015). Springer Proceedings in Advanced Robotics
DOI: 10.1007/978-3-319-60916-4_32
Link to Publication

Abstract:
Sampling-based planning is a common method for solving motion planning problems. However, this paradigm falters in difficult scenarios, such as narrow passages. In contrast, humans can frequently identify these challenges and can sometimes propose an approximate solution. A recent method called Region Steering takes advantage of this intuition by allowing a user to define regions in the workspace to weight the search space for probabilistic roadmap planners. In this work, we extend Region Steering into a generalized Region-Based framework that is suitable for any sampling-based planning approach. We explore three variants of our framework for graph-based, tree-based, and hybrid planning methods. We evaluate these variants in simulations as a proof of concept. Our results demonstrate the benefits of our framework in reducing overall planning time. 

@inbook{Denny-agrffc-2018, 
 address = {Cham}, 
 author = {Denny, Jory 
and Sandstr{\"o}m, Read 
and Amato, Nancy M.}, 
 booktitle = {Robotics Research: Volume 2}, 
 doi = {10.1007/978-3-319-60916-4_32}, 
 editor = {Bicchi, Antonio 
and Burgard, Wolfram}, 
 isbn = {978-3-319-60916-4}, 
 pages = {563--579}, 
 publisher = {Springer International Publishing}, 
 title = {A General Region-Based Framework for Collaborative Planning}, 
 url = {https://doi.org/10.1007/978-3-319-60916-4_32}, 
 year = {2018} 
}