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Efficient Optical Localization for Mobile Robots via Kalman Filtering-Based Location Prediction

[+] Author Affiliations
Jason N. Greenberg, Xiaobo Tan

Michigan State University, East Lansing, MI

Paper No. DSCC2016-9917, pp. V002T23A009; 9 pages
  • ASME 2016 Dynamic Systems and Control Conference
  • Volume 2: Mechatronics; Mechatronics and Controls in Advanced Manufacturing; Modeling and Control of Automotive Systems and Combustion Engines; Modeling and Validation; Motion and Vibration Control Applications; Multi-Agent and Networked Systems; Path Planning and Motion Control; Robot Manipulators; Sensors and Actuators; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamic Controls; Vehicle Dynamics and Traffic Control
  • Minneapolis, Minnesota, USA, October 12–14, 2016
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5070-1
  • Copyright © 2016 by ASME


Localization and communication are both essential functionalities of any practical mobile sensor network. Achieving both capabilities through a single Simultaneous Localization And Communication (SLAC) would greatly reduce the complexity of system implementation. In this paper a technique for localizing a mobile agent using the line of sight (LOS) detection of an LED-based optical communication system is proposed. Specifically, in a two-dimensional (2D) setting, the lines of sight between a mobile robot and two base nodes enable the latter to acquire bearing information of the robot and compute its location. However, due to the mobile nature of the robot, establishing its LOS with the base nodes would require extensive scan for all parties, severely limiting the temporal resolution and spatial precision of the localization. We propose the use of a Kalman filter to predict the position of the robot based on past localization results, which allows the nodes to significantly reduce the search range in establishing LOS. Simulation results and preliminary experimental results are presented to illustrate and support the proposed approach.

Copyright © 2016 by ASME



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