[1]WU Ming,SUN Ji-yin.An interacting multiple model filtering algorithm for mobile robots to improve tracking of moving objects in unknown environments[J].CAAI Transactions on Intelligent Systems,2010,5(2):127-138.
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An interacting multiple model filtering algorithm for mobile robots to improve tracking of moving objects in unknown environments

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 2 Page number: 127-138 Column: 学术论文—机器感知与模式识别 Public date: 2010-04-25
Title:
An interacting multiple model filtering algorithm for mobile robots to improve tracking of moving objects in unknown environments
Author(s):
WU Ming;  SUN Ji-yin
Department of Computer, The Second Artillery Engineering College, Xi’an 710025, China
Keywords:
interacting multiple model filter;  extended Kalman filter;  simultaneous localization and mapping;  object tracking; mobile robot
CLC:
TP242.6
DOI:
-
Abstract:
A novel method was developed for synchronous localization and mapping (SLAM) and object tracking (OT) to provide simultaneous estimation of a robot’s and any object’s trajectories in an unknown environment. The system was based on interacting multiple model (IMM) filtering. In this approach, the states of robots, objects and landmarks were used to form an integrated system state. A full covariance extended Kalman filter (EKF) was then employed to estimate system state. As the iterative estimation progressed, sufficient correlations between the different objects in the system could be establish to reflect the interdependent relationships of estimations between different system objects. In this way the precision of object state estimation was improved. Moreover, when combined with a traditional IMM filter algorithm, this method solved the uncertainty problem for modes of object motion. With the application of IMM, the method helped robots to track objects and estimate their modes of motion, improving the accuracy of object localization. Simulation results validated the effectiveness of the proposed method in the estimation of the trajectories of robots and objects and the modes of motion of tracked targets. 
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