Title: A mixed model data association for simultaneous localisation and mapping in dynamic environments

Authors: Rex H. Wong; Jizhong Xiao; Samleo L. Joseph; Shouling He

Addresses: Department of Engineering and Technology, Vaughn College of Aeronautics and Technology, New York, NY 11369, USA ' Department of Electrical Engineering, The City College of the City University of New York, New York, NY 10031, USA ' Department of Electrical Engineering, The City College of the City University of New York, New York, NY 10031, USA ' Department of Engineering and Technology, Vaughn College of Aeronautics and Technology, New York, NY 11369, USA

Abstract: This paper presents a feasible and robust approach which handles the real-time data association problem for robotic simultaneous localisation and mapping (SLAM) in clutter and dynamic environment. Unlike most of proposals that are based on a single model to estimate the dynamics of a scenario and thus fall short of the variation of environmental complexity which may need different models to estimate the modes of behaviour, in this paper, we propose an integrated schema which mixes the interactive multiple model (IMM) and joint probabilistic data association (JPDA), with the asymmetric assignment optimisation algorithm to generate the optimal feasible hypothesis. Because of its adaptability and cost-effectiveness, this approach can be applied for real-time SLAM applications. Simulation is performed to demonstrate the effectiveness of this method.

Keywords: interactive multiple models; IMM; joint probabilistic data association; JPDA; simultaneous localisation and mapping; SLAM; clutter; asymmetric assignment optimisation; robot localisation; robot mapping; mobile robots; indoor environments; object avoidance; robot navigation; simulation; dynamic environments; modelling.

DOI: 10.1504/IJMA.2013.052614

International Journal of Mechatronics and Automation, 2013 Vol.3 No.1, pp.1 - 15

Received: 03 Apr 2012
Accepted: 24 Aug 2012

Published online: 30 Apr 2014 *

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