Fly Robot Interface (Neural). NeuRob
Krapp Lab · Department of Bioengineering, Imperial College London
View Our Report
Motivation
Biology
is
significantly
more
energy-efficient
than
traditional
computing
For Our Project
We have leveraged a bio-inspired brain-machine interface (BMI) system that uses visual neurons from blowflies (Calliphora vicina) to control wheeled robots in real time. This system converts H1 neuron optical flow signals into motion commands, mimicking how insects avoid obstacles.
Project Overview
This project applies insect visual systems—specifically H1 neurons—toward robot control. We used real-time neural recordings to steer robots with more than 90% obstacle avoidance accuracy.
Technical Highlights
Real-time insect neuron signals for robot control
Optical flow response simulating natural obstacle avoidance
Dual H1 neuron fusion for expanded perception
Custom 3D-printed platform for enhanced stability
Scalable to complex obstacle avoidance systems
Before & After Improvement
Team Members
Supervisors
Prof. Holger Krapp
Professor of Sensory and Motor Neuroscience at Imperial College London.
Dr. Jiaqi Huang
Research Associate at Imperial College London. Working on biohybrid robotic system based on insect vision in Krapp Lab.
Project Members
Zeyuan Xin
Yuichiro Minamikawa
Jiaowen Jun
Shuchang Zhang
