Pac-Man Pete：VEXロボティクスでAIを構築するための拡張可能なフレームワーク
Pac-Man Pete: An extensible framework for building AI in VEX Robotics
VEXロボティクス競技向けに、Unityシミュレーションと強化学習、コンピュータビジョン、外部計算オフロードを組み合わせた自律ロボットのフレームワークを開発し、コミュニティに公開した。
著者: Jacob Zietek, Nicholas Wade, Cole Roberts, Aref Malek, Manish Pylla, Will Xu, Sagar Patil
分類: cs.RO, cs.AI, cs.LG
原文アブストラクト
This technical report details VEX Robotics team BLRSAI's development of a fully autonomous robot for VEX Robotics' Tipping Point AI Competition. We identify and develop three separate critical components. This includes a Unity simulation and reinforcement learning model training pipeline, a malleable computer vision pipeline, and a data transfer pipeline to offload large computations from the VEX V5 Brain/micro-controller to an external computer. We give the community access to all of these components in hopes they can reuse and improve upon them in the future, and that it'll spark new ideas for autonomy as well as the necessary infrastructure and programs for AI in educational robotics.