Multi-scale Instrumentation of Biological Swarms
Engineers draw inspiration from biological swarms when designing multi-agent systems, from software to robotics. Advances in our understanding of natural swarms are therefore essential to technological advancement. Biological swarms are challenging to study for many of the reasons that robotic swarms are challenging to design.
They are complex systems with nonlinear interactions among individual agents which sense, signal and actuate locally while distributed in cluttered environments. Empirical investigations of biological swarms and the environments that they operate in often require measurement tools with sufficient spatial and temporal resolution to observe the experience and behavior of individuals and the collective simultaneously. Recent focus on multi-scale empirical investigations of biological swarms has led many research teams to develop custom technologies and analysis pipelines (e.g., computer vision software, sensor arrays, automated experiments) that are tailored for their specific study systems. This special session on multi-scale instrumentation of biological swarms will promote interactions among these groups which are facing similar challenges.
The paper/presentation format will be the same as regular DARS-SWARMS sessions, stay posted for details.
Please contact us with any questions [jmp547 / kirstin at cornell dot edu]
Jacob Peters (Cornell University): Peters completed his PhD in Organismic and Evolutionary Biology at Harvard University in 2018 with Dr. Stacey Combes and Dr. L. Mahadevan, and is now a Postdoctoral Fellow with Kirstin Petersen at Cornell University. His research combines experimental and computational approaches to understand distributed control of complex physical tasks performed by honeybee colonies. These tasks include self-organized nest ventilation and collective control of mechanical and thermal stability in honeybee swarm clusters. These behaviors highlight the ability of animal groups to use existing physical phenomena in fluid dynamics, elastomechanics and thermodynamics to integrate locally-sourced information and elicit group-level responses. Recently, my work has led me to explore how these concepts can be used in engineered systems such as multi-agent robotic systems and active materials.
Kirstin Petersen (Cornell University): Petersen’s research is focused on design and coordination of bio-inspired robot collectives and studies of their natural counterparts. She graduated from Harvard University and the Wyss Institute for Biologically Inspired Engineering in 2014, completed a postdoc at the Max Planck Institute for Intelligent Systems in 2016, and started the Collective Embodied Intelligence Lab in 2016 as part of the Electrical and Computer Engineering department at Cornell University. Petersen’s research was ranked among Science Magazine’s Top 10 Scientific Achievements of 2014, she was among Robohub’s Top 25 Women in Robotics to Know About in 2018, and received the Packard Fellowship for Science and Engineering in 2019.
Support for this special session comes from the National Science Foundation, grants #1739671 and the Cornell Institute of Digital Agriculture 2019 RIF Award.