Semantic Trajectory Planning on the Edge for Optimized Context-Aware Autonomous Navigation of Mobile Robots

Abstract

Autonomous mobile transport systems are a key enabler for flexible production organization. In order to enhance the software life cycle management and the overall function range, service-based offloading of software function towards cloud and edge is a valid alternative to monolithic onboard software architectures. We introduce an approach towards an edge-computing-based improvement of the classic autonomous navigation stack in terms of considering semantic policies using visual object detection and localization. Thus, context-aware navigation in regards to safety and efficiency can be implemented, e.g. to fulfill directions of standards and guidelines for production, hospital or public domains.