Building embodied AI from spiking neurons — one breakthrough at a time.
The Freenove robot dog has a problem. It drifts to the right. Every unit is different — servo tolerances, weight distribution, surface friction — and no amount of calibration fixes…
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A 560-Neuron Spiking Network Steers a Quadruped Toward Light For the first time, MH-FLOCKE’s robot dog actively navigates toward a light source in simulation — driven by hardwired reflexes and…
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The Freenove robot dog can now navigate to targets on its own. No external reward, no reward shaping, no supervision. It sniffs, turns, runs, and finds what it’s looking for…
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Today we replaced the mathematical heart of MH-FLOCKE’s locomotion system. The old Central Pattern Generator — a set of sine and cosine functions that produced smooth, predictable gait patterns —…
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A 232-neuron spiking neural network learns obstacle avoidance through cerebellar error correction. 9 bugs, 8 runs, and the first-ever CPG→SNN handoff in MH-FLOCKE history.
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The Brain3D visualization in MH-FLOCKE’s rendered videos now shows the actual cerebellar architecture — not an abstract network graph, but the real populations with their correct sizes and live spike…
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MH-FLOCKE now runs on a real robot. A Freenove Robot Dog Kit (~100€) with a Raspberry Pi 4 executes the same spiking neural network that learns to walk in the…
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Architecture Deep Dive · March 22, 2026 · MH-FLOCKE Level 15 v0.4.x Every reinforcement learning tutorial starts the same way: define a reward function. Want the robot to walk? Reward…
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Dev Log #1 · March 22, 2026 · MH-FLOCKE Level 15 v0.4.x For weeks, the dog walked beautifully but ignored the ball completely. It would stroll past it, around it,…
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