Robot Cooperation on Peer Reciprocal Learning and IoT-based Automatic Packaging

Abstract

In this dissertation we propose two systems of robot cooperation a robot peer reciprocal learning system and an Internet-of-Things (IoT)-based automatic e-fulfillment packaging system based on two different perspectives The robot peer reciprocal learning system is inspired by human peer learning theories In this system similar function robots are treated as learning partners they can not only cooperatively accomplish difficult tasks but also help each other to learn better For learning a new concept we also propose a mutual concept learning method which allows the robots to learn from each other by exchanging weights in their neural network concept learning system On the other hand the IoT-based automatic e-fulfillment packaging system is an implementation of the concept of Industry 4 0 In the system all components are connected and monitored by a cyber network and cooperatively accomplish a packaging task in a warehouse e-fulfillment situation For packing all items inside a suitably sized box we propose a 3D Adaptive Particle Swarm Optimization (PSO)-based packing algorithm Finally the simulations and the experiments demonstrate the efficiency of the proposed robot cooperation systems and learning algorithms

Date of Award	2017 Jun 9
Original language	English
Supervisor	Tzuu-Hseng S. Li (Supervisor)