Bashar Badr is a research student working in the Electronic Systems Design research group of the department. His research focuses on Hardware Implementation of Decision Trees for Robotic Applications
Expertise
Machine learning
Keywords
machine learning
Real-time Incremental learning
Hardware-based machine learning for mobile robot navigation
The project will involve applying decision tree methods to mobile robot navigation systems to allow them to learn and make appropriate movement decisions. The project will take existing approaches developed at Loughborough and implement these in an FPGA-based system to achieve high speed parallel solution that is able to learn and react rapidly while consuming little power, few hardware resources and having limited payload. The project will investigate single and multiple robot systems, the latter using a networking approach to build a co-ordinated view of the robots' environment.
View all Mr Badr’s publications in the central publications database
Selected Publications
[1] Bashar E. Badr, and David J. Mulvaney, Hardware Implementation of Decision Trees for Robotic Applications, Research Conference 2010, RSSE, Loughborough University, May 2010
[2] Bashar E. Badr, David J. Mulvaney, and Vassilios A. Chouliaras, Implementation of Decision Trees in a Configurable Multiprocessor Architecture in VLSI-SOC 2011: Proceedings of the 19th IFIP/IEEE International Conference on Very Large Scale Integration 2011, Kowloon, Hong Kong, China, Oct. 3-5, 2011.
(Paper and poster)
