Intelligent exploration of unknown environments with vision like sensors Conference Paper

abstract

• In this work we present a methodology for intelligent path planning in an uncertain environment using vision like sensors. We show that the problem of path planning can be posed as the adaptive control of an uncertain Markov decision process. The strategy for path planning then reduces to computing the control policy based on the current estimate of the environment, also known as the "certainty equivalence" principle in the adaptive control literature. We propose a Monte-Carlo based estimation scheme, incorporating non local sensors, for estimating the probabilities of the environment process, which significantly accelerates the convergence of the associated path planning algorithms. 2005 IEEE.

name of conference

• Proceedings, 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

authors

• Chakravorty, Suman
• Junkins, John

published proceedings

• 2005 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS, VOLS 1 AND 2

author list (cited authors)

• Chakravorty, S., & Junkins, J. L.

citation count

• 4

complete list of authors

• Chakravorty, S||Junkins, JL

publication date

• January 2005

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• n2159-6255ISSN  Journal

keywords

• Acceleration
• Adaptive Control
• Convergence
• Intelligent Sensors
• Mobile Robots
• Motion Planning
• Optimal Control
• Path Planning
• Programmable Control
• Uncertainty

Digital Object Identifier (DOI)

• 10.1109/aim.2005.1511174

International Standard Book Number (ISBN) 10

• 0-7803-9046-6

start page

• 1204

end page

• 1209

volume

• 2

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Faim.2005.1511174