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Neuromorphic control for optic-flow-based landings of MAVs using the Loihi processor
However, a major challenge for using such processors on robotic platforms is the reality gap between simulation and the real world.
Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks
We focus on the complex task of learning to estimate optical flow from event-based camera inputs in a self-supervised manner, and modify the state-of-the-art ANN training pipeline to encode minimal temporal information in its inputs.
Fully neuromorphic vision and control for autonomous drone flight
Robotic experiments show a successful sim-to-real transfer of the fully learned neuromorphic pipeline.
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