Autonomous Toy Truck Steered by Eight Artificial Neurons
In an exciting development in the world of artificial intelligence, a team at the Global Science Network (GSN) has successfully created an autonomous RC truck using a Spiking Neural Network (SNN). This innovative technology processes sensor input signals as discrete spike events through a hardware neural network, allowing the RC truck to navigate and manoeuvre on its own.
The GSN SNN 4-8-24-2 Autonomous Vehicle, as it's named, is equipped with four proximity sensors (front, front-left, front-right, and rear). These sensors transmit their readings wirelessly to the artificial brain, an SNN made up of eight artificial neurons. Each sensor input feeds into the corresponding neuron, and the neurons communicate via excitatory or inhibitory synapses, controlling spike timing and firing rates.
The SNN processes these spike inputs and outputs commands to the truck, determining its movement such as going forward, backward, or turning. These commands are sent back wirelessly to the truck by hacking the remote control circuitry. The network’s operation is observable via LEDs indicating neuron activity, which aids understanding of the SNN's internal dynamics.
In addition to the RC truck demonstration, GSN has also released videos showing a digital squid's behaviour shaped by a neural network on their channel. This further demonstrates the broader application of such SNNs in behaviour control.
The key principle in SNNs is that both the timing of spikes and signal strength matter, unlike traditional neural networks that use continuous values. This innovative approach allows for more complex and nuanced behaviour in the controlled systems.
For those interested in learning more, the key video for the RC truck is titled "Artificial Brain Controlled RC Truck", published by Global Science Network, showcasing the autonomous operation and explaining the SNN concept visually alongside the vehicle’s behaviour.
This project combines hardware SNN implementation, simple sensor arrays, and hacked RF remote controls to demonstrate autonomous navigation and behaviour control in small robotic platforms. The GSN SNN 4-8-24-2 Autonomous Vehicle is a significant step forward in the development of autonomous robotic systems and the application of SNN technology.
[1] Global Science Network. (n.d.). Artificial Brain Controlled RC Truck. [Video file]. YouTube. https://www.youtube.com/watch?v=1eB867yD_74
[2] Global Science Network. (n.d.). Digital Squid Behavior Controlled by Neural Network. [Video file]. YouTube. https://www.youtube.com/watch?v=zvOW4l_iP4M
[3] Global Science Network. (n.d.). Spiking Neural Networks Explained. [Video file]. YouTube. https://www.youtube.com/watch?v=jCi8I1JlE1Q
[4] Global Science Network. (n.d.). Spiking Neural Networks. [Website]. https://www.globalscience.network/spiking-neural-networks
- The Global Science Network's (GSN) creation, the GSN SNN 4-8-24-2 Autonomous Vehicle, utilizes artificial intelligence, space-and-astronomy technology, and sensors to function autonomously, featuring four proximity sensors that transmit their readings to an artificial brain made up of eight artificial neurons.
- The broader application of such Spiking Neural Networks (SNN) is showcased by GSN, as demonstrated in videos on their channel, including the digital squid's behavior shaped by a neural network and the "Artificial Brain Controlled RC Truck" video, which explains how the SNN technology processes spike inputs to control the vehicle's movement.
