Method for tracking of environmental level sets by a unicycle-like vehicle

Authors:
Alexey S. Matveev;Hamid Teimoori;Andrey V. Savkin
Affiliations:
Department of Mathematics and Mechanics, Saint Petersburg University, Universitetskii 28, Petrodvoretz, St.Petersburg, 198504, Russia;School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney 2052, Australia;School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney 2052, Australia
Venue:
Automatica (Journal of IFAC)
Year:
2012

Citing 7
Cited 0

A dual-space approach to tracking and sensor management in wireless sensor networks

WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
A biologically inspired method for vision-based docking of wheeled mobile robots

Robotics and Autonomous Systems
ACE in the Hole: Adaptive Contour Estimation Using Collaborating Mobile Sensors

IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Experimental validation of cooperative environmental boundary tracking with on-board sensors

ACC'09 Proceedings of the 2009 conference on American Control Conference
Equiangular navigation and guidance of a wheeled mobile robot based on range-only measurements

Robotics and Autonomous Systems
Boundary estimation in sensor networks: theory and methods

IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
A biologically inspired method for robot navigation in a cluttered environment

Robotica

Quantified Score

Hi-index	22.14

Visualization

Abstract

We consider a single Dubins-like vehicle traveling with a constant longitudinal speed in a planar region supporting an unknown field distribution. A sensor provides the distribution value at the vehicle location. We present a new sliding mode control method for tracking environmental level sets: the vehicle is steered to the set where the distribution assumes a pre-specified value and circulates along this set afterwards. The proposed control algorithm does not employ gradient estimation and is non-demanding with respect to both computation and motion. Its mathematically rigorous justification is provided. The effectiveness of the proposed guidance law is confirmed by computer simulations.