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Abstract: Visual inertial odometry (VIO) is a technique to estimate the change of a mobile platform in position and orientation over time by using the measurements from on-board cameras and IMU sensor. Recently VIO attracts significant attentions from large number of researchers and is gaining the popularity in various potential applications due to the miniaturization in size and low cost in price of two sensing modularities. However, it is very challenging in both of technical development and engineering implementation when accuracy, real time performance, robustness, and operation scale are taken into consideration. This talk is to report the state of the art VIO techniques from the perspectives of filtering and optimisation based approaches, which are two dominated approaches adopted in the research area. Various filtering based approaches optimisation based approaches are introduced and their link will be clarified. Some video clips will be demonstrated during the talk.

Dongbing Gu¼òÀú: Dongbing Gu is a 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 180 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 International Journal of Model, Identification, and Control, Cognitive Computations, Intelligent Industrial Systems, and Frontiers Robotics and AI. He served as a member of organizing committee and programme committee for many international conferences. Prof. Gu is a senior member of IEEE.