Generalized Polyhedral Object Recognition and Localization Using Crossbeam Sensing

Object localization is a fundamental task in industrial automa tion. In this article, we present a recognition and localization technique based upon binary beam sensors. Binary beam sen sors, which consist of modulated LED light sources and de tectors, are appropriate for manufacturing applications due to their reliability, high accuracy, robustness, inexpensiveness, and ease of calibration. By extracting sufficient information, recognition and localization can be performed as fast (~ 0.1 s) and as accurately (~ 25 microns) as high-speed manufactur ing requires. Generalized polyhedral objects are recognized and localized by being passed through a crossbeam sensor which is a set of coplanar oriented binary light-beam sensors; robot positions are recorded when the beam sensors' outputs change. Recognition and localization share two subproblems: the correspondence problem (the problem of interpreting the sensed features in terms of the model features), and the pose- estimation problem (the problem of estimating the object's pose from the sensed data and an interpretation of the sensed fea tures in terms of model features). In Wallack and Manocha (1994), we described a pose-estimation technique for crossbeam sensor data. In this article, we present two methods for solving the correspondence problem for crossbeam sensor data: a lin ear time completely on-line method, and a constant-time on-line method that utilizes preprocessing.