Towards Bio-inspired Estimation and Control for Autonomous Systems: Lessons from Collective Animal Behavior
Talk Abstract: Collective animal behavior provides numerous examples of robust coordination and decision-making in complex environments. Fish schools, in particular, perform navigation and aggregation tasks by integrating noisy visual and hydrodynamic cues and propagating this information across the group. This makes them a natural model system for studying decentralized estimation and control problems for multi-agent systems. This talk will present recent theoretical advances in modeling and analyzing fish behavior through the lens of dynamical systems and control theory. I will introduce a data-driven framework that combines potential flow approximations with stochastic differential equations to characterize hydrodynamic coupling, sensory fusion, and their feedback into locomotor control. I will show how this framework leads to novel zero-order optimization strategies for autonomous robotic navigation in unknown environments and provides a quantitative description of the feedback control process underlying predator-prey interactions. I will conclude by outlining emerging directions in multi-agent inference and collective decision-making informed by biological principles.
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- 94 Brett Road
- Piscataway, New Jersey
- United States 08854
- Building: Rutgers Busch Campus - Electrical Engineering Building
- Room Number: Conference Room, EE 240
- Click here for Map
- Starts 17 November 2025 05:00 AM UTC
- Ends 03 December 2025 12:00 AM UTC
- No Admission Charge
Speakers
Daniel Burbano
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Biography:
Dr. Burbano received the B.Sc. in Electronic Engineering and the M.Sc. in Industrial Automation from the National University of Colombia (2010, 2012), and the Ph.D. in Control Engineering from the University of Naples Federico II, Italy (2015). He has been a Postdoctoral Researcher at Northwestern University and a Faculty Fellow at New York University and is currently an Assistant Professor of Electrical and Computer Engineering at Rutgers University. Dr. Burbano is the recipient of the NSF CAREER Award. He serves as a Senior Associate Editor for IEEE Transactions on Circuits and Systems II (TCAS II) and as an Editor for PLoS Complex Systems. His research interests encompass the analysis and control of complex systems and networks, with a focus on data-driven modeling, network inference, and collective decision-making in animal groups.
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Agenda
5:15 pm snacks and meet the speaker
5:30 pm Talk