Grid-based localization and local mapping with moving object detection and tracking

Trung-Dung Vu (1) , Julien Burlet (1) , Olivier Aycard (2)

1 E-MOTION - Geometry and Probability for Motion and Action
2 AMA - Analyse de données, Modélisation et Apprentissage automatique [Grenoble]

We present a real-time algorithm for simultaneous localization and local mapping (local SLAM) with detection and tracking of moving objects (DATMO) in dynamic outdoor environments from a moving vehicle equipped with a laser scanner, short-range radars and odometry. To correct the vehicle odometry we introduce a new fast implementation of incremental scan matching method that can work reliably in dynamic outdoor environments. After obtaining a good vehicle localization, the map surrounding of the vehicle is updated incrementally and moving objects are detected without a priori knowledge of the targets. Detected moving objects are finally tracked by a Multiple Hypothesis Tracker (MHT) coupled with an adaptive Interacting Multiple Model (IMM) filter. The experimental results on datasets collected from different scenarios such as: urban streets, country roads and highways demonstrate the efficiency of the proposed algorithm.

Domaines: Robotique [cs.RO]

Trung-Dung Vu, Julien Burlet, Olivier Aycard. Grid-based localization and local mapping with moving object detection and tracking. Information Fusion, 2011, 12 (1), pp.58-69. ⟨10.1016/j.inffus.2010.01.004⟩. ⟨hal-01023076⟩