Vision-based path construction and maintenance for indoor guidance of autonomous ground vehicles based on collaborative smart cameras

Abstract

In this paper, we present a guidance and coordination of autonomous ground vehicles in indoor environment. The solution is based on a set of distributed ceiling-mounted smart cameras with overlapping field-of-view for global coordination. A mean shift based algorithm is implemented to extract a map of the environment. This map is used for a distributed routing of autonomous-guided-vehicles from source to destination. Shortest paths will be calculated and updated in real-time. Our approach fits the requirements of decentralized coordination, real-time environmental changes, as it is the case in production facilities, and portability to other fields of application. First, tests in a test-bench showed satisfying results in terms of reliability, validity and performance.