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Paper TuB05.5

Surana, Amit (UTRC), Mathew, George (United Technologies Research Center), Kannan, Suresh (United Technologies Research Center)

Coverage Control of Mobile Sensors for Adaptive Search of Unknown Number of Targets

Scheduled for presentation during the Regular Session "Sensor Networks" (TuB05), Tuesday, May 15, 2012, 11:30−11:45, 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 December 11, 2017

Keywords Path Planning for Multiple Mobile Robots or Agents, Surveillance Systems, Aerial Robotics

Abstract

We present a multiscale adaptive search algorithm for efficiently searching an unknown number of stationary targets using a team of multiple mobile sensors. We first derive a Spectral Multiscale Coverage (SMC) control law for a Dubins vehicle model. Given a search prior, the SMC control gives rise to uniform coverage dynamics for the mobile sensors such that the amount of time spent observing a region is proportional to finding a target in it. In order to make the search robust to sensor uncertainties and Automatic Target Detection algorithm errors (i.e. false alarm, missed detections), we combine the SMC control with decision and estimation theoretic techniques. As new targets are discovered we use the Sequential Ratio Probability Test and Recursive Least Squares estimation to quantify the current uncertainty in target detection and location, respectively. This uncertainty is used to update the search prior so as to balance exploitation (reduce uncertainty in state of already discovered potential targets) and exploration (discover new targets). We demonstrate this adaptive search methodology in a high fidelity simulation environment and show an improved performance over lawnmower type search.

 

 

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