Balancing bot using Neuroevolution

In a series of previous posts I’ve discussed setting up and training a controller for a balancing bot using reinforcement learning. In this post I’m going to discuss another technique called neuroevolution for the same task. Neuroevolution optimizes parameters of an artificial neural network using an evolutionary algorithm. Parameters may refer to weights of the network,

Autonomous driving at the micro scale

Building and training a self-driving robocar takes several iterations of hardware and software improvements. Especially training a competitive model is a time consuming process that involves going back-and-forth to the track several times to either check or improve model predictive performance by recording additional samples. Computer simulation is an alternative, however setting up a simulation

Setup Raspberry Pi as a 5GHz Access Point

When in the field testing autonomous vehicles, a required but often tedious task consists of setting up a network and connecting all devices. Usually this consists of at least three devices: The rover, the base station, and optionally an access point to create and manage the network. Since the platform that I’m working on, Burro,

Updates to Burro self-driving platform

I’ve been busy implementing some cool updates to Burro, the self-driving RC car/robot platform I’m building. Here’s a summary: The Adafruit Motor HAT is now supported in addition to NAVIO2. Both boards are fully supported , and in fact you can use the same SD card in different cars/robots, without the need to reinstall anything, as