ScholarlyCommons

Title

Clustering-Based Robot Navigation and Control

Author(s)

Omur Arslan, University of PennsylvaniaFollow
Dan P. Guralnik, University of PennsylvaniaFollow
Daniel E. Koditschek, University of PennsylvaniaFollow

Image

Abstract

In robotics, it is essential to model and understand the topologies of configuration spaces in order to design provably correct motion planners. The common practice in motion planning for modelling configuration spaces requires either a global, explicit representation of a configuration space in terms of standard geometric and topological models, or an asymptotically dense collection of sample configurations connected by simple paths. In this short note, we present an overview of our recent results that utilize clustering for closing the gap between these two complementary approaches. Traditionally an unsupervised learning method, clustering offers automated tools to discover hidden intrinsic structures in generally complex-shaped and high-dimensional configuration spaces of robotic systems. We demonstrate some potential applications of such clustering tools to the problem of feedback motion planning and control. In particular, we briefly present our use of hierarchical clustering for provably correct, computationally efficient coordinated multirobot motion design, and we briefly describe how robot-centric Voronoi diagrams can be used for provably correct safe robot navigation in forest-like cluttered environments, and for provably correct collision-free coverage and congestion control of heterogeneous disk-shaped robots.

For more information: Kod*lab

Sponsor Acknowledgements

This work was supported in part by AFOSR under the CHASE MURI FA9550–10–1−0567.

Document Type

Conference Paper

Subject Area

GRASP, Kodlab

Date of this Version

5-16-2016

Publication Source

2016 IEEE International Conference on Robotics and Automation, Workshop on Emerging Topological Techniques in Robotics

Keywords

Motion planning, Clustering, Configuration spaces, Topology, Sampling-based motion planning

Bib Tex

@Misc{arslan_guralnik_kod_ICRA2016TopologyWorkshop, Title = {Clustering-Based Robot Navigation and Control}, Author = {Omur Arslan and Dan P. Guralnik and Daniel E. Koditschek}, Booktitle = {Robotics and Automation, 2016 IEEE International Conference on, Workshop on Emerging Topological Techniques in Robotics}, Year = {2016} }