# Japanese researchers train robot swarms using single-robot imitation learning

> **Key takeaway:** Researchers demonstrated that up to 40 Raspberry Pi-based robots can learn coordination behaviors from demonstrations of a single robot, without inter-robot communication or external positioning.

**Published:** 2026-10-21T13:57:24+00:00 
**Source:** Hackster.io News 
**Category:** open-hardware 
**Canonical URL:** https://fosswire.org/news/japanese-researchers-train-robot-swarms-using-single-robot-i.html 

## Summary
A team from Japan's National Institute of Advanced Industrial Science and Technology, Institute of Science Tokyo, and University of Tokyo developed an imitation learning approach for multi-robot coordination. Using a lightweight 2.4-million-parameter neural network running on Raspberry Pi 4 hardware, groups of wheeled robots learned to collect and push blocks in a shared workspace. The robots operate independently with only forward-facing cameras, processing visual input at 5 Hz without GPU acceleration.

## How the swarm learns from one
- **Hardware platform**: Raspberry Pi Mouse V3, 14 cm wide, with Raspberry Pi 4 and Camera Module 3
- **Neural network**: MobileNetV2 for visual processing, mixture-of-experts with two LSTM-based expert networks and a routing network
- **Model size**: 2.4 million parameters, runs on CPU without GPU acceleration
- **Control rate**: 5 Hz velocity command generation from camera observations
- **Training data**: Human joystick demonstrations of single robot, with two conditions—stationary background robots or autonomously moving background robots
- **Scale tested**: Up to 40 robots in 3.5-meter-square workspace with 28 orange blocks

## Why it matters
The approach lowers the data collection barrier for swarm robotics by eliminating the need for multi-robot teleoperation, though congestion limits and the difficulty of learning from moving-robot demonstrations indicate significant scaling challenges remain before practical deployment.