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Paper TuB210.4

Twigg, Jeffrey (Army Research Lab), Fink, Jonathan (ARL), Yu, Paul (ARL), Sadler, Brian (Army Research Laboratory)

RSS Gradient-Assisted Frontier Exploration and Radio Source Localization

Scheduled for presentation during the Interactive Session "Interactive Session TuB-2" (TuB210), Tuesday, May 15, 2012, 11:00−11:30, Ballroom D

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 October 15, 2018

Keywords Networked Robots, Mapping

Abstract

We consider the combined problem of frontier exploration in a complex indoor environment while seeking a radio source. To do this in an efficient manner, we incorporate radio signal strength (RSS) information into the exploration algorithm by locally sampling the RSS and estimating the 2-D RSS gradient. The algorithm exploits the local motion to collect RSS samples for gradient estimation and seeks to explore in a way that brings the robot to the signal source. This strategy avoids random or exhaustive exploration. An indoor experiment demonstrates the exploration algorithm that uses this information to dynamically prioritize candidate frontiers and traverse to a radio source. Simulations, including radio propagation modeling with a ray-tracing algorithm, enable study of control algorithm tradeoffs and statistical performance.

 

 

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