Abstract
In previous work, we developed a decentralized framework for formation control by mobile robots. Each robot simultaneously estimates the current swarm shape, by local information diffusion in a communication network, while controlling its own motion to drive the swarm to the desired shape. These continuous-time estimation and control laws result in provably correct behavior, but they make unrealistic assumptions for implementation on actual robots.
This paper describes the first experimental implementation of decentralized estimation and control based on information diffusion. We develop the hardware, software, and communication protocols that adapt the theoretical approach to an actual implementation. Experiments demonstrate that the robots successfully estimate the first and second inertial moments of the swarm, using scalable local communication, while simultaneously moving to control these moments.
Related Journals
Related Books
Computational Intelligence For Data Analysis
Machine Learning and Its Application: A Quick Guide for Beginners
Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
A First Course in Artificial Intelligence
Artificial Intelligence: Models, Algorithms and Applications
Advanced Computing Techniques: Implementation, Informatics and Emerging Technologies
Handbook of Mobile Application Development: A Guide to Selecting the Right Engineering and Quality Features
Ad Hoc and Sensor Wireless Networks: Architectures, Algorithms and Protocols
Applications of Modern High Performance Networks
Arduino Meets Matlab: Interfacing, Programs and Simulink