Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning
Novak Zagradjanin, Aleksandar Rodić, Dragan Pamučar, Bojan Pavković
Abstract
This paper considers an autonomous cloud-based multi-robot system designed to execute highly repetitive tasksin a dynamic environment such as a modern megastore. Cloud level is intended for performing the most demandingoperations in order to unload the robots that are users of cloud services in this architecture. For path planningon global level D* Lite algorithm is applied, bearing in mind its high efficiency in dynamic environments. In orderto introduce smart cost map for further improvement of path planning in complex and crowded environment, implementationof fuzzy inference system and learning algorithm is proposed. The results indicate the possibility ofapplying a similar concept in different real-world robotics applications, in order to reduce the total paths length,as well as to minimize the risk in path planning related to the human-robot interactions.