IEEE-CT RAS/CS/IAS Meeting - Lecture "Autonomous Control of Aerial Robots for Environmental Monitoring"


The IEEE RAS/CS/IAS Connecticut chapter will present a guest lecture from Dr. Nikolay Atanasov titled "Autonomous Control of Aerial Robots for Environmental Monitoring", on Wednesday, March 24th from 7:30-8:30PM virtually via Google Meet. All IEEE members and Non-IEEE members are welcome to this event. Feel free to spread the word to your colleagues and friends.

  Date and Time




  • Date: 24 Mar 2021
  • Time: 07:30 PM to 08:30 PM
  • All times are US/Eastern
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Join with Google Meet

Join by Phone:(US) +1 458-216-0412‬ PIN: ‪739 543 783‬#

  • Hartford, Connecticut
  • United States 06106

  • Chapter chair, Dr. Kevin Huang,

    Co-chair, Professor Haoyu Wang,

  • Starts 08 March 2021 05:00 AM
  • Ends 24 March 2021 08:00 PM
  • All times are US/Eastern
  • No Admission Charge


Nikolay Atanasov

Nikolay Atanasov of University of California San Diego, Department of Electrical and Computer Engineering


Autonomous Control of Aerial Robots for Environmental Monitoring

This talk will present techniques for persistent monitoring and online mapping of outdoor terrain using unmanned aerial vehicles (UAVs) to aid wildfire detection. We will discuss real-time mapping of terrain geometry and semantics (e.g., trees, grass, buildings) using Gaussian Process regression and Graph Convolutional Networks. Techniques for planning dynamically feasible flight trajectories to enable coverage of environment areas of interest will also be presented.


Nikolay A. Atanasov is an Assistant Professor at the Department of Electrical and Computer Engineering, University of California San Diego, CA, USA. His research focuses on robotics, control theory, and machine learning and in particular on autonomous information collection using ground and aerial robots for localization and mapping, environmental monitoring, and security and surveillance. He works on probabilistic map models that unify geometry and semantics and on optimal control and reinforcement learning techniques for minimizing uncertainty in these models. Dr. Atanasov's work has been recognized by the Joseph and Rosaline Wolf award for the best Ph.D. dissertation in Electrical and Systems Engineering at the University of Pennsylvania in 2015 and the best conference paper award at the International Conference on Robotics and Automation in 2017.