ICRA 2012 Paper Abstract

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Paper WeC07.5

Atanasov, Nikolay (University of Pennsylvania), Le Ny, Jerome (University of Pennsylvania), Michael, Nathan (University of Pennsylvania), Pappas, George J. (University of Pennsylvania)

Stochastic Source Seeking in Complex Environments

Scheduled for presentation during the Regular Session "Environment Mapping" (WeC07), Wednesday, May 16, 2012, 15:30−15:45, Meeting Room 7 (Remnicha)

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 February 23, 2018

Keywords Autonomous Agents, Autonomous Navigation, Field Robots

Abstract

The objective of source seeking problems is to determine the minimum of an unknown signal field, which represents a physical quantity of interest, such as heat, chemical concentration, or sound. This paper proposes a strategy for source seeking in a noisy signal field using a mobile robot and based on a stochastic gradient descent algorithm. Our scheme does not require a prior map of the environment or a model of the signal field and is simple enough to be implemented on platforms with limited computational power. We discuss the asymptotic convergence guarantees of algorithm and give specific guidelines for its application to mobile robots in unknown indoor environments with obstacles. Both simulations and real-world experiments were carried out to evaluate the performance of our approach. The results suggest that the algorithm has good finite time performance in complex environments.

 

 

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