Homotopy-aware RRT: Toward human-robot topological path-planning

• Published in: 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI) pp. 279 - 286
• Main Authors: Yi, Daqing, Goodrich, Michael A., Seppi, Kevin D.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.03.2016
• Subjects: Algorithms; Computational modeling; Computer science; Conferences; Electronic mail; Heuristic algorithms; Human; Human-robot interaction; Information dissemination; Interactive; Optimization; Robots; Shape; Topology
• ISSN: 2167-2148
• DOI: 10.1109/HRI.2016.7451763

An important problem in human-robot interaction is for a human to be able to tell the robot go to a particular location with instructions on how to get there or what to avoid on the way. This paper provides a solution to problems where the human wants the robot not only to optimize some objective but also to honor “soft” or “hard” topological constraints, i.e. “go quickly from A to B while avoiding C”. The paper presents the HARRT* (homotopy-aware RRT*) algorithm, which is a computationally scalable algorithm that a robot can use to plan optimal paths subject to the information provided by the human. The paper provides a theoretic justification for the key property of the algorithm, proposes a heuristic for RRT*, and uses a set of simulation case studies of the resulting algorithm to make a case for why these properties are compatible with the requirements of human-robot interactive path-planning.