ClipBot: an educational, physically impaired robot that learns to walk via genetic algorithm optimization

TL;DR

ClipBot is an educational, low-cost robot made of paper clips that learns to walk through genetic algorithm optimization, demonstrating how AI can overcome hardware limitations in a simple, hands-on learning environment.

Contribution

This paper introduces ClipBot, a novel DIY educational robot that uses genetic algorithms to learn walking despite mechanical impairments, facilitating hands-on AI learning.

Findings

Robot learned to walk in less than 20 iterations

Genetic algorithm effectively optimized movement despite hardware limitations

Educational use demonstrated in high school setting

Abstract

Educational robots allow experimenting with a variety of principles from mechanics, electronics, and informatics. Here we propose ClipBot, a low-cost, do-it-yourself, robot whose skeleton is made of two paper clips. An Arduino nano microcontroller actuates two servo motors that move the paper clips. However, such mechanical configuration confers physical impairments to movement. This creates the need for and allows experimenting with artificial intelligence methods to overcome hardware limitations. We report our experience in the usage of this robot during the study week 'fascinating informatics', organized by the Swiss Foundation Schweizer Jugend Forscht (www.sjf.ch). Students at the high school level were asked to implement a genetic algorithm to optimize the movements of the robot until it learned to walk. Such a methodology allowed the robot to learn the motor actuation scheme yielding straight movement in the forward direction using less than 20 iterations.