ICRA 2012 Paper Abstract

Close

Paper TuC05.6

Williams, Ryan (University of Southern California), Sukhatme, Gaurav (University of Southern California)

Probabilistic Spatial Mapping and Curve Tracking in Distributed Multi-Agent Systems

Scheduled for presentation during the Regular Session "Multi-Robot Systems 1" (TuC05), Tuesday, May 15, 2012, 15:45−16:00, Meeting Room 5 (Ska)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on November 14, 2018

Keywords Distributed Robot Systems, Mapping, Networked Robots

Abstract

In this paper we consider a probabilistic method for mapping a spatial process over a distributed multi-agent system and a coordinated level curve tracking algorithm for adaptive sampling. As opposed to assuming the independence of spatial features (e.g. an occupancy grid model), we adopt a novel model of spatial dependence based on the grid-structured Markov random field that exploits spatial structure to enhance mapping. The multi-agent Markov random field framework is utilized to distribute the model over the system and to decompose the problem of global inference into local belief propagation problems coupled with neighbor-wise inter-agent message passing. A Lyapunov stable control law for tracking level curves in the plane is derived and a method of gradient and Hessian estimation is presented for applying the control in a probabilistic map of the process. Simulation results over a real-world dataset with the goal of mapping a plume-like oceanographic process demonstrate the efficacy of the proposed algorithms. Scalability and complexity results suggest the feasibility of the approach in realistic multi-agent deployments.

 

 

Technical Content © IEEE Robotics & Automation Society

This site is protected by copyright and trademark laws under US and International law.
All rights reserved. © 2002-2018 PaperCept, Inc.
Page generated 2018-11-14  07:26:22 PST  Terms of use