Algorithms for the Safe Management of Autonomous Vehicles

Abstract

We deal here with a fleet of autonomous vehicles which is required to perform internal logistics tasks inside some protected area. This fleet is supposed to be ruled by a hierarchical supervision architecture, which, at the top level distributes and schedules Pick up and Delivery tasks, and, at the lowest level, ensures safety at the crossroads and controls the trajectories. We focus here on the top level, while introducing a time dependent estimation of the risk induced by the traversal of any arc at a given time. We set a model, state some structural results, and design, in order to route and schedule the vehicles according to a well-fitted compromise between speed and risk, a bi-level algorithm and a A* algorithm which both relies on a reinforcement learning scheme.

Room mapping system using RFID and mobile robots

“…A UTONOMOUS navigation robots are currently the subject of much research, and the RFID technique [1], [2], [3] is often used in experimental developments as part of a robot navigation and indoor mapping system [4], [5]. Such systems are used to identify objects with passive or semipassive tags equipped with a writable memory with an information capacity far superior to the currently used barcodes [1].…”