Research

Reinforcement learning; multi robot learning; adaptive control; robot control; system identification and estimation. Investigation of methods of computer learning, with focus on robotic applications. Algorithms related to methods of reinforcement learning, fuzzy control, system identification and estimation are developed to automatically adjust and adapt robot behaviour. Robots learn how to work together and how to compete. Ideas associated with genetic algorithms and game theory are also being investigated.

Application

Working with industry in enhancing robot situational awareness for bomb disposal robots. Applications in the use of robots for perimeter security. We are working with industrial partners in developing learning models for cellular network synchronization. Robots learn how to work together and how to compete for applications in security, mapping and search and rescue.

Activities

• TPC member for the International Conference on Control and Applications (2010 and 2011)
• Chair of Session on Machine Learning at the American Control Conference (2011)

Journal Articles

Howard M. Schwartz, and John M. Daly (2008), “An Approach to Output Feedback Adaptive Control For Robot Manipulators,” International Journal of Robotics and Automation, Vol. 23, No. 3, pp. 168-176, 2008 .

Xiaosong Lu, and Howard M. Schwartz (2008), “A Revised Adaptive Fuzzy Sliding Mode Controller for Robotic Manipulators,” International Journal of Modelling, Identification and Control, Vol. 4, No. 2, pp.127-133, 2008 .

Sidney N. Givigi, and Howard M. Schwartz (2007), “Swarm Robot Systems based on the Evolution of Personality Traits,” Turkish Journal of Electrical Engineering and Computer Sciences (Elektrik): Special Issue on Swarm Robotics 15(2): 257-282.

A.N. Campbell, and H.M. Schwartz (2007), “Multiple Model Control Improvements: Hypothesis Testing and Modified Model Arrangement,” Control and Intelligent Systems 35(3): 236-243.

Conference Publications

Desouky, Sameh F. and Schwartz, Howard M., “A Novel Hybrid Learning Technique Applied to a Self-Learning Multi-Robot System “, Proceedings of the IEEE Conference on Systems, Man and Cybernetics, Oct. 11 – 14, 2009.

Desouky, Sameh F. and Schwartz, Howard M., “A Novel Technique to Design a Fuzzy Logic Controller Using Q(λ)-Learning and Genetic Algorithms in The Pursuit-Evasion Game “, Proceedings of the IEEE Conference on Systems, Man and Cybernetics, Oct. 11 – 14, 2009.

Desouky, Sameh F. and Schwartz, Howard M., “Hybrid Intelligent Systems Applied to The Pursuit-Evasion Game “, Proceedings of the IEEE Conference on Systems, Man and Cybernetics, Oct. 11 – 14, 2009.

Givigi, Sidney N., Schwartz, Howard M. and Lu, Xiaosong, “An Experimental Adaptive Fuzzy Controller for Differential Games. “, Proceedings of the IEEE Conference on Systems, Man and Cybernetics, Oct. 11 – 14, 2009.

Desouky, Sameh F. and Schwartz, Howard M., “Genetic Based Fuzzy Logic Controller For a Wall-Following Mobil Robot “, Proceedings of the American Control Conference, St. Louis, Missouri, June 10 – 12, 2009.

Howard M. Schwartz, and Sidney N. Givigi, “A Practical Approach to Robotic Swarms,” International Conference on Control and Applications, May 2008.

Sidney N. Givigi, and Howard M. Schwartz, “Swarm Formation Viewed as A Differential Game,” International Conference on Control and Applications, Quebec City, May 2008.

Sidney N. Givigi, and Howard M. Schwartz, “Swarms of Robots Based on Evolutionary Game Theory,” International Conference on Control and Applications, May 2007.

Xiaosong Lu, and Howard M. Schwartz, “An Investigation of Adaptive Fuzzy Sliding Mode Control for Robotic Manipulators,” International Conference on Control and Applications, May 2007.

Howard M. Schwartz, and Shafiqul Islam, “An Evaluation of Adaptive Robot Control via Velocity Estimated Feedback,” International Conference on Control and Applications, May 2007.