Research Area / Fields

  1. Planning under uncertainty and AI
  2. Semantic perception and simultaneous localization and mapping (SLAM)
  3. Multi-robot systems

Short Bio

Vadim Indelman is currently an Associate Professor in the Department of Aerospace Engineering at the Technion – Israel Institute of Technology, and he is also a member of the Technion Autonomous Systems Program (TASP), the Technion Artificial Intelligence Hub (Tech.AI), and the Israeli Smart Transportation Research Center (ISTRC). Additionally, he is a member of the European Laboratory for Learning and Intelligent Systems (ELLIS). He is currently leading the Robotics vertical at TechAI, which promotes and facilitates research activities and projects within the Technion and collaboration with industry in areas related to AI and robotics. Dr. Indelman is the founder and head of the Autonomous Navigation and Perception Lab (ANPL), which performs research related to single and multi-robot autonomous perception, navigation and planning under uncertainty in the context of mobile robotics. His current research interests include planning under uncertainty, probabilistic inference, semantic perception and simultaneous localization and mapping (SLAM) in single and multi-robot systems.

Prior to joining the Technion as a faculty member, he was a postdoctoral fellow in the Institute of Robotics and Intelligent Machines (IRIM) at the Georgia Institute of Technology (between 2012 and 2014). He obtained his Ph.D. degree in Aerospace Engineering at the Technion in 2011, and also holds B.A. and B.Sc. degrees in Computer Science and Aerospace Engineering, respectively, both awarded by the Technion in 2002. Dr. Indelman was an Associate Editor for the IEEE Robotics and Automation Letters (RA-L), an Editor for IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), and a co-chair of the IEEE Robotics and Automation Society Technical Committee on Algorithms for the Planning and Control of Robot Motion.

Available Technologies for commercialization

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