Avionics for sub-gram aerial robots
Sensor fusion with a compact, lightweight and power-efficient sensor suite
The aim here is to achieve sensor autonomy to obtain state feedback necessary for closed-loop attitude, altitude and lateral velocity control. A sensor suite comprising a gyroscope, optical flow sensor and a laser rangefinder (or a barometer) provides a measurement model that satisfies the observability criteria. Kalman filter variants are suitable for sensor fusion, and the estimates can then be fed into a controller such as PID or LQR.
While inertial measurement units (IMU), laser rangefinders and barometers are available at a low enough weight (~ 15mg), commercially available optical flow sensors widely used in conventional drones are too heavy (> 120 mg) for this work. To solve this, we utilize a monochrome global shutter imaging sensor paired with a sufficiently small lens and implement a highly optimized optical flow algorithm based on the Lucas-Kanade method.
Key specs:
- weight including microcontroller: 97 mg
- dimensions after folding: < 1 x 1 x 0.5 cm^3^
- estimation (driven by IMU sampling frequency) at 500 Hz
- customized optical flow estimation at 100 Hz
- Low-latency real-time wireless data transmission
Prior published work: (Yu et al., 2025), (Talwekar et al., 2022)
Pushing further: gyroscope free visual-inertial flight control for 10-mg robots
Due to the physics at the small scale, under free-flight, accelerometers can be used to estimate the drag force acting on the robot, which in turn can provide lateral velocity information. Combined with a camera, we can formulate an estimator for attitude and velocity control inspired by the wind-vision sensor fusion in the fruit fly Drosophila melanogaster. Work published in Science Robotics (Fuller et al., 2022)