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Title: Dynamic Prediction-Based Optical Localization of a Robot During Continuous Movement
Abstract

Localization of mobile robots is essential for navigation and data collection. This work presents an optical localization scheme for mobile robots during the robot’s continuous movement, despite that only one bearing angle can be captured at a time. In particular, this paper significantly improves upon our previous works where the robot has to pause its movement in order to acquire the two bearing angle measurements needed for position determination. The latter restriction forces the robot to work in a stop-and-go mode, which constrains the robot’s mobilitty. The proposed scheme exploits the velocity prediction from Kalman filtering, to properly correlate two consecutive measurements of bearing angles with respect to the base nodes (beacons) to produce location measurement. The proposed solution is evaluated in simulation and its advantage is demonstrated through the comparison with the traditional approach where the two consecutive angle measurements are directly used to compute the location.

 
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Award ID(s):
1734272
NSF-PAR ID:
10310737
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Proceedings of ASME 2020 Dynamic Systems and Control Conference
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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