The Cognitive Optimization and Relational (CORE) Robotics laboratory develops advanced algorithmic techniques to enable robots to collaborate with human teammates. The lab’s work is founded upon the vision for moving beyond thinking of robots as tools that must be manually controlled towards a paradigm in which robots can learn through interaction and experience how to be effective peers for human professionals in healthcare, manufacturing, and search & rescue. Algorithmic techniques include deep reinforcement learning, mathematical programming, and distributed control theory. Additionally, we conduct human subject experiments to understand how to design effective algorithms and to evaluate the contribution of our computational techniques.
- Dec 4, 2019 – Zheyuan Wang’s preprint “Learning to Dynamically Coordinate Multi-Robot Teams…” is out on archive.
- October 11, 2019 – Matthew Gombolay gave keynote for the Southeastern Robotics Symposium.
- October 1, 2019 – Nakul Gopalan joins the lab. Welcome!
- September 13, 2019 – Matthew Gombolay receives NASA Early Career Fellowship on “Scaling the Power of the Astronaut via Workload-aware Robotic Apprenticeship and Explainable Autonomy”.
- August 15, 2019 – New members Andrew Silva, Laura Strickland, Erin Hedlund, Pradyumna Tambwekar, Sam Yi Ting, Van Duong, and Zayra Lobo join the lab. Welcome!