Prof. Shaojie Shen and his research team Won the 2023 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award for their paper "RACER: Rapid Collaborative Exploration with a Decentralized Multi-UAV System".

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Prof. Shaojie Shen and his research team Won the 2023 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award for their paper "RACER: Rapid Collaborative Exploration with a Decentralized Multi-UAV System".

 

We are pleased to share the news that Professor Shaojie Shen and his research team have been awarded the 2023 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award. Their far-reaching work, titled "RACER: Rapid Collaborative Exploration with a Decentralized Multi-UAV System," authored by Boyu Zhou, Hao Xu, and Professor Shen, has been recognized for its groundbreaking contribution to the field of robotics. The first author, Boyu Zhou, was PhD student supervised by Prof. SHEN during 2018-2022 and is currently an Assistant Professor at Sun Yat-sen University. Hao Xu completed PhD degree at HKUST in 2023.

 

The award will be officially presented at the 2024 IEEE International Conference on Robotics and Automation (ICRA), taking place in Yokohama, Japan. Further details about the conference can be found on the official website at https://2024.ieee-icra.org/. The paper, featured in the June 2023 issue of IEEE Transactions on Robotics, (Volume 39, Issue 3, Pages 1816-1835), outlines the RACER system, which presents a revolutionary framework for enhancing collaborative unmanned aerial vehicle (UAV) missions through a decentralized approach. The full paper is available for review on IEEE Xplore. We extend our warmest congratulations to Professor Shen and his team on this remarkable achievement. Previously, Prof. Shen's research group has received Honorable Mention in IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award twice for VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator(2018) and "Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments"(2020).

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