Automatic sensor placement for model-based robot vision.
This paper presents a method for automatic sensor placement for model-based robot vision. In such a vision system, the sensor often needs to be moved from one pose to another around the object to observe all features of interest. This allows multiple three-dimensional (3-D) images to be taken from different vantage viewpoints. The task involves determination of the optimal sensor placements and a shortest path through these viewpoints. During the sensor planning, object features are resampled as individual points attached with surface normals. The optimal sensor placement graph is achieved by a genetic algorithm in which a min-max criterion is used for the evaluation. A shortest path is determined by Christofides algorithm. A Viewpoint Planner is developed to generate the sensor placement plan. It includes many functions, such as 3-D animation of the object geometry, sensor specification, initialization of the viewpoint number and their distribution, viewpoint evolution, shortest path computation, scene simulation of a specific viewpoint, parameter amendment. Experiments are also carried out on a real robot vision system to demonstrate the effectiveness of the proposed method.
Chen
S Y
SY
Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Kowloon, Hong Kong. mesychen@cityu.edu.hk
Li
Y F
YF
D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D010780:Photogrammetry / Q000295:instrumentation / Q000379:methods*; D012371:Robotics / Q000295:instrumentation / Q000379:methods*; D014159:Transducers