A Floyd-Dijkstra hybrid application for mobile robot path planning in life science automation

Abstract

A new application for path planning is presented for mobile robot transportation in life science laboratories. In this application: (a) to decide the shortest paths for mobile tasks, a hybrid path planning strategy using two algorithms from the map theory is proposed. The Floyd algorithm is adopted to do an off-line path planning, and the Dijkstra algorithm is executed to decide an on-line alternative path when the Floyd based route is not available. Different to intelligence based planning methods (such as Artificial Neural Networks), the map theory based methods can definitely guarantee a global shortest path based on the prepared waypoints. This is important for a big life science environment; (b) besides the path planning issue, other main contents for mobile transportation are elaborated, including task dispatching, robot localization, communication architecture, XML-based command protocol, etc. Two experiments show that the proposed application and its developed software are effective for mobile robot transportation in life science laboratories.