NDLI: Moving Obstacles Detection and Camera Pointing for Mobile Robot Applications

Content Provider	ACM Digital Library
Author	Larnier, Stanislas Devy, Michel Achour, Nouara Lakrouf, Mustapha
Abstract	Perception is one of the most important tasks for safe navigation of autonomous mobile robots in outdoor environments that are dynamic and unknown. This paper presents a real time system for detection and classification of dynamic objects using a 2D laser range finder (2D LRF) and a moving camera mounted on the mobile robot. An occupancy grid based detection is implemented using 2D LRF and moving objects are iteratively extracted from the global occupancy grid. A visual classification system is developed using HOG features and AdaBoost as learning process. Dynamic objects detection and visual classification results are coupled to point moving camera on the specified target (specified by mission supervisor) and to identify it. Finally, real time experiments results on the mobile robot in two different scenarios are presented.
Starting Page	57
Ending Page	62
Page Count	6
File Format	PDF
ISBN	9781450352802
DOI	10.1145/3068796.3068816
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-02-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Moving objects detection Occupancy grid Visual classification and pedestrian detection
Content Type	Text
Resource Type	Article

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Moving Obstacles Detection and Camera Pointing for Mobile Robot Applications