Institute of Robotics and Automatic Information System
Seminar Series：Advanced Robotics & MEMS
题目：Gaussian Process Approaches for Environment Monitoring with Autonomous Robots
单位：University of Essex, UK（埃塞克斯大学）
Abstract: Spatio-temporal function regression is critical for environmental monitoring. Mobile robots with equipped sensors provide a capability to reconstruct a spatio-temporal function over the area of interest. This talk introduces a Gaussian process regression approach to the spatio-temporal regression problem and a locational optimization algorithm for the collective motion control of mobile robots. Gaussian process regression will use a hierarchical framework to factor the joint distribution of complex processes into a series of simple conditional models. The locational optimization algorithm will use a Voronoi tessellation based algorithm to enable the robots to cover the monitored area. The talk will also show some simulated results and related project in our group.
Bio: Dongbing Gu is professor in School of Computer Science and Electronic Engineering, University of Essex, UK. His current research interests include distributed control algorithms, distributed information fusion, cooperative control, model predictive control, and machine learning. He has published more than 120 papers in international conferences and journals. His research has been supported by Royal Society, EPSRC, EU FP7, British Council, and industries. He is a board member of Internal Journal of Model, Identification and Control. He served as a member of organizing committee for 13 international conferences, and a member of programme committee for over 100 international conferences. He is a regular reviewer for over 50 international journals. Prof. Gu now is a senior member of IEEE, member of technical committee of the IEEE Safety, Security and Rescue Robotics and member of Robotics Task Force of the Intelligent Systems Applications Technical Committee (ISATC) in the IEEE Computational Intelligence Society (IEEE/CIS).