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Members of the lab at the Robotics Science and Systems (RSS) Conference in Freiburg, Germany. June 2019.

Members of the lab celebrating a birthday! June 2019.

Katie showing a robot to children at the Museum of Science and Industry. April 2019.

Rab demonstrating her experiment at the Museum of Science and Industry. April 2019.

National Robotics Week at the Museum of Science and Industry. April 2019.

Ola showing off the Nao robot at the Museum of Science and Industry. April 2019.

Members of the lab at the Workshop on Algorithmic Robotics (WAFR) Conference in Merida, Mexico. December 2018.

About

In the Interactive and Emergent Autonomy Lab, our research focuses on computational methods in data-driven control, information theory in physical systems, and embodied intelligence. We investigate how both autonomous systems and biological systems interact with their environments (and, in some cases, with each other) to learn and improve their behaviors. This work often involves mathematical modeling, development of new mathematical tools, algorithmic implementation and programming, and experimentation.

News

April 24, 2021 Giorgos's work on derivative-based Koopman operators gets accepted to IEEE T-RO

March 26, 2021 Paper on Autotuning MPC and ergodic imitation both get accepted to ICRA 2021

February 22, 2021 Rab defends her PhD thesis

January 01, 2021 Tommy and Alex part of Low rattling: A predictive principle for self-organization in active collectives paper in Science

November 20, 2020 Todd participates in panel on responsibility in AI

November 11, 2020 Katie defends PhD thesis and starts job at Penn State

October 01, 2020 Muchen Sun joins the Murphey Lab

September 25, 2020 Giorgos publishes paper in NeurIPS 2020

September 22, 2020 Paper on animal exploration with Chen Chen and Malcolm MacIver comes out in eLife

Recent Papers

Derivative-Based Koopman Operators for Real-Time Control of Robotic Systems
G. Mamakoukas, M. Castano, X. Tan, T. D. Murphey
IEEE Transactions on Robotics (TRO), 2021. Article

Automatic Tuning for Data-driven Model Predictive Control
W. Edwards, G. Tang, G. Mamakoukas, T. D. Murphey, K. Hauser
IEEE Int. Conf. on Robotics and Automation (ICRA), 2021. Article

Ergodic imitation: Learning from what to do and what not to do
A. Kalinowska, A. Prabhakar, K. Fitzsimons, T. D. Murphey
IEEE Int. Conf. on Robotics and Automation (ICRA), 2021. PDF

Low Rattling: A Predictive Principle for Self-Organization in Active Collectives
P. Chvykov, T. A. Berrueta, A. Vardhan, W. Savoie, A. Samland, T. D. Murphey, K. Wiesenfeld, D. I. Goldman, and J. L. England
Science, vol. 371, no. 6524, 2021. Article

Algorithmic Design for Embodied Intelligence in Synthetic Cells
A. Pervan and T. D. Murphey
IEEE Transactions on Automation Science and Engineering (T-ASE), 2020. PDF