NDLI: Parameter Estimation and Threat Localization Using Multiple Robots With Kinematic Constraints

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Deshpande, Sagar Smith, Philip Hui, Qing
Copyright Year	2012
Abstract	In this paper we present a simple heuristic approach to localize and estimate the parameters of unknown threat sources by use of kinematically constrained sensing robots. Since the distributed sensor robots cannot always be guided by a human it becomes imperative to impart decision making ability to the robots so they navigate themselves through the area of interest to determine the most information about the threats. We achieve this by using the current data collected by robots to generate a rough estimate of the threat parameters via a nonlinear least squares fit of the data collected by robots. We assume that the threat’s dispersion surface can be represented by a superposition of radial basis functions. We develop and test a heuristic algorithm for moving the robots to improve our surface estimate. In general, this requires some of the robots to move towards each of the threat sources while exploring area between these sources. As the motion progresses we update and improve our estimate of the threat surface thus allowing us to refine the paths of the robots for additional data collection. This approach is studied in detail with extensive simulations and results are presented. Our goal is to most efficiently recover the parameters of the threat surface within the least time.
Sponsorship	Dynamic Systems and Control Division
Starting Page	719
Ending Page	725
Page Count	7
File Format	PDF
ISBN	9780791845301
DOI	10.1115/DSCC2012-MOVIC2012-8554
Volume Number	Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems
Conference Proceedings	ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
Language	English
Publisher Date	2012-10-17
Publisher Place	Fort Lauderdale, Florida, USA
Access Restriction	Subscribed
Subject Keyword	Parameter estimation Algorithms Simulation Decision making Kinematics Data collection Surface roughness Engineering simulation Sensors Robots
Content Type	Text
Resource Type	Article

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