ROBUST 3-D OBJECT DETECTION AND FEATURE EXTRACTION FOR MULTI-ROBOT COOPERATION
This paper develops a computer vision system for multi-robot cooperation in rescue operations. The work is focused on providing robust and fast vision capabilities to the robots to meet the expected level of performance. Enhanced versions of existing techniques and new techniques are utilized to develop an adaptive vision system architecture for use in an unstructured environment of multi-robot activity in an emergency scenario. Different types of object detection methods are selected in real time in the developed system according to the requirements of a robot. To validate the developed system for use in a multi-robot application, rigorous experiments are conducted in a typical unstructured environment. Features such as invariance of scale, rotation, illumination, and occlusion are tested with different types of objects, for various methods. Generally, good results are obtained.