A General Region-Based Framework for Collaborative Planning

Jory Denny, Read Sandström, Nancy M. Amato

Research output: Chapter in Book/Report/Conference proceedingChapter


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.

Original languageEnglish (US)
Title of host publicationSpringer Proceedings in Advanced Robotics
Number of pages17
StatePublished - 2018
Externally publishedYes

Publication series

NameSpringer Proceedings in Advanced Robotics
ISSN (Print)2511-1256
ISSN (Electronic)2511-1264

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Engineering (miscellaneous)
  • Artificial Intelligence
  • Computer Science Applications
  • Applied Mathematics


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