Geometric Relation-Based Cognitive Sharing for Flying and Ground Mobile Robot Cooperation

Abstract

Cognitive sharing of objects is fundamental in a heterogeneous robot system composed of a Unmanned Aerial Vehicle and a ground robot. Since the viewpoint of a UAV is greatly different from a ground robot, they may have different perceptions about the same objects. That makes it difficult to realize cognitive sharing. In this paper, we proposed a cognitive sharing method which is based on Geometric Relation-based Triangle Representations. The method is able to make a UAV and a ground robot identify the same object from similar objects without sharing appearance information in unstructured environment. To copy with the problem of increasing computational cost for the recognition of objects in the Region of Interest, entropy evaluation is employed to evaluate and select unique representations. We illustrated the proposed method with robots in real world.