Sensor placement design for object pose determination with three light-stripe range finders

Abstract

The pose (position and orientation) of a polyhedral object can be determined with range data obtained from simple light-stripe range finders. However, localization results are sensitive to where those range finders are placed in the workspace, that is, sensor placement. It is advantageous for vision tasks in a factory environment to plan optimal sensing positions off-line all at once rather than online sequentially. This paper presents a method for finding an optimal sensor placement off-line to accurately determine the pose of an object when using three light-stripe range finders. We evaluate a sensor placement on the basis of average performance measures such as an error rate of object recognition, recognition speed and pose uncertainty over the state space of object pose by a Monte Carlo method. An optimal sensor placement which is given a maximal score by a scalar function of the performance measures is selected by another Monte Carlo method. We emphasize that the expected performance of our system under an optimal sensor placement can be characterized completely via simulation.