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Paper WeA07.6

Kodaka, Kenri (Waseda University), Ogata, Tetsuya (Kyoto University), Sugano, Shigeki (Waseda University)

Rhythm-based Adaptive Localization in Incomplete RFID Landmark Environments

Scheduled for presentation during the Regular Session "SLAM I" (WeA07), Wednesday, May 16, 2012, 09:45−10:00, Meeting Room 7 (Remnicha)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on February 23, 2018

Keywords Localization, Wheeled Robots, Learning and Adaptive Systems

Abstract

This paper proposes a novel hybrid-structured model for the adaptive localization of robots combining a stochastic localization model and a rhythmic action model, for avoiding vacant spaces of landmarks efficiently. In regularly arranged landmark environments, robots may not be able to detect any landmarks for a long time during a straight-like movement. Consequently, locally diverse and smooth movement patterns need to be generated to keep the position estimation stable. Conventional approaches aiming at the probabilistic optimization cannot rapidly generate the detailed movement pattern due to a huge computational cost; therefore a simple but diverse movement structure needs to be introduced as an alternative option. We solve this problem by combining a particle filter as the stochastic localization module and the dynamical action model generating a zig-zagging motion. The validation experiments, where virtual-line-tracing tasks are exhibited on a floor-installed RFID environment, show that introducing the proposed rhythm pattern can improve a minimum error boundary and a velocity performance for arbitrary tolerance errors can be improved by the rhythm amplitude adaptation fed back by the localization deviation.

 

 

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