The authors proposed a method to generate steering parameter for automatic vehicle guidance in wheeled mobile robots by using human experience. This human-based method uses a database that learns behavior of a human driver by processing forward scene. The database system learns how to operate steering wheel related to scene of curved lane from operation of the human driver, and the sets of profile of lane and angle of steering wheel are stored into database. Then, it recognizes lane and picks up database item that has similar lane profile. The steering parameter was generated from those items. In order to build the database system, the authors designed and fabricated a vehicle equipped with three CCD cameras, angular pickup of steering wheel, vehicle velocity sensor, etc. The steering data were converted to sets of colored rectangles of on the screen. In order to synchronize captured images with steered information, they were combined into one video image by using video quad switcher, and the series of each combined image were recorded with the VTR. First, the learning process was performed by using the database system. Next, the generation process was at tempted. The proposed generation method was applied to unknown, inexperienced road. Experiments were carried out and algorithms for generating steering parameters were tested. The experiments showed good results, and our method generated steering parameters that were almost same as ones obtained from human driver. The generation in object avoidance was performed with good accuracy also.
A generation method of control parameters for visual navigation in wheeled mobile robots
Ein Verfahren zur Generierung von Regelungsparametern für die visuelle Navigation autonomer Fahrzeuge
MechRob, Mechatronics and Robotics, 2004 ; 290-295
2004
6 Seiten, 15 Bilder, 13 Quellen
Conference paper
English
Visual navigation of wheeled mobile robots using direct feedback of a geometric constraint
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