Title
Designing Autonomous Flying Robots From Insect Behavior – Engineering and Robotics
Mentor
Floris van Breugel, Ph.D.
Department
Mechanical Engineering
Bio sketch
We study insects for inspiration in designing robust and novel control systems for robots. Our lab uses real time tracking, high speed video, and virtual reality to study freely moving animals. Then, aided by modern machine learning tools and control theory, we analyze the behavior, and implement the principles on robotic systems. Along the way, we use genetic tools available in the fruit fly to gain insight into how brains function.
Project overview
Current algorithms for controlling autonomous robots generally rely on continuous estimation algorithms that fuse visual and inertial sensory modalities to build accurate state estimates. These methods, however, are too computationally expensive to implement on the smallest flying robots. Our lab takes inspiration from insects to develop novel estimation methods for autonomous flying robots to estimate key values more efficiently and accurately, like wind direction, ground speed, and distance to nearby obstacles. Ongoing research projects include testing our theoretical algorithms on a real-world quadrotor platform.
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