Burak is a Ph.D. student in the University of Washington’s Department of Aeronautics & Astronautics. He is part of Kristi Morgansen’sNonlinear Dynamics and Control lab. Burak is researching how the hawkmoth (Manduca sexta) senses the environment. He says: “Hawkmoths are amazing. They’re extremely good at agile maneuvers and we’re trying to understand how such a small insect can be that clever.” The goal is that this information will inform how to build engineered systems that can sense more precisely and efficiently.
Researchers from the University of Washington, Carnegie Mellon University, and the Massachusetts Institute of Technology have been awarded a 2019 multidisciplinary university research initiative (MURI) award from the Air Force Office of Scientific Research to investigate neural-inspired sparse sensing and control for agile flight. The MURI program supports teams of investigators from different fields to facilitate the growth of newly emerging technologies.
This MURI, on Neural-inspired Sparse Sensing and Control for Agile Flight, is led by University of Washington Associated Professor of Biology Bing Brunton, and involves Tom Daniel, Steve Brunton, and Nathan Kutz from the University of Washington, Sarah Bergbreiter from Carnegie Mellon, and Jonathan How from MIT.
The work of this MURI is inspired by the fact that flying animals are superbly adapted to acquire and process information about themselves and the environment to control their movement in an exceedingly complex and dynamic world. They do so over a vast range of temporal and spatial scales. Importantly, the micro-circuits in insect neural systems operate under stringent constraints of size, weight, and power. In stark contrast with many modern engineered systems, these remarkable motor behaviors for flight are achieved not by brute-force computation and learning, but rather with specialized hardware and relatively sparse neuronal computations. Therefore, sparsity is a central concept in understanding neural control of agile flight, where it serves as a mathematical framework to promote hyper-efficient solutions and to achieve robust sensing and control.
In this MURI, we seek understanding of and inspiration from living systems, which provide proof by existence that sparse sensing, processing, and computation can achieve remarkably agile and rapid flight control in complex, nonlinear, and uncertainty environments. Our multi-institute team of researchers combines expertise in sensory biology, systems neuroscience, machine learning, sparse optimization, control theory, sensor design, and robotics.
