Web-Gewu: A Browser-Based Interactive Playground for Robot Reinforcement Learning

TL;DR

Web-Gewu is a browser-based platform that enables low-cost, real-time robot reinforcement learning education by offloading simulation and training to edge nodes, eliminating the need for local hardware or extensive cloud resources.

Contribution

It introduces a scalable, low-cost, web-based robotics education system utilizing WebRTC for peer-to-peer streaming and edge computing for simulation and RL training.

Findings

Enables real-time interaction with robots in browsers without local installation.

Reduces hardware and bandwidth costs compared to traditional cloud solutions.

Provides scalable and barrier-free robotics education infrastructure.

Abstract

With the rapid development of embodied intelligence, robotics education faces a dual challenge: high computational barriers and cumbersome environment configuration. Existing centralized cloud simulation solutions incur substantial GPU and bandwidth costs that preclude large-scale deployment, while pure local computing is severely constrained by learners' hardware limitations. To address these issues, we propose \href{http://47.76.242.88:8080/receiver/index.html}{Web-Gewu}, an interactive robotics education platform built on a WebRTC cloud-edge-client collaborative architecture. The system offloads all physics simulation and reinforcement learning (RL) training to the edge node, while the cloud server acts exclusively as a lightweight signaling relay, enabling extremely low-cost browser-based peer-to-peer (P2P) real-time streaming. Learners can interact with multi-form robots at low end-to-end latency directly in a web browser without any local installation, and simultaneously observe real-time visualization of multi-dimensional monitoring data, including reinforcement learning reward curves. Combined with a predefined robust command communication protocol, Web-Gewu provides a highly scalable, out-of-the-box, and barrier-free teaching infrastructure for embodied intelligence, significantly lowering the barrier to entry for cutting-edge robotics technology.