ICRA 2011 Paper Abstract

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Paper ThP110.4

Dong-Si, Tue-Cuong (University of California, Riverside), Mourikis, Anastasios (University of California, Riverside)

Motion Tracking with Fixed-Lag Smoothing: Algorithm and Consistency Analysis

Scheduled for presentation during the Regular Sessions "Localization III" (ThP110), Thursday, May 12, 2011, 14:25−14:40, Room 5E

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on May 22, 2019

Keywords Localization, Sensor Fusion, Autonomous Navigation

Abstract

This paper presents a fixed-lag smoothing algorithm for tracking the motion of a mobile robot in real time. The algorithm processes measurements from proprioceptive (e.g., odometry, inertial measurement unit) and exteroceptive (e.g., camera, laser scanner) sensors, in order to estimate the trajectory of the vehicle. Smoothing is carried out in the information-filtering framework, and utilizes iterative minimization, which renders the method well-suited for applications where the effects of the measurements' nonlinearity are significant. The algorithm attains constant computational complexity by marginalizing out older states. The key contribution of this work is a detailed analysis of the effects of the marginalization process on the consistency properties of the estimator. Based on this analysis, a linearization scheme that results in substantially improved accuracy, compared to the standard linearization approach, is proposed. Both simulation and real-world experimental results are presented, which demonstrate that the proposed method attains localization accuracy superior to that of competing approaches.

 

 

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