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

2026-04-18 · Kaixuan Chen, Linqi Ye arxiv

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.

📄 PDF Abstract BibTeX arXiv:2604.17050

Code (0)

등록된 구현이 없습니다.

Tasks

Reinforcement Learning

Federated Learning Playground

2026-02-23 · Bryan Shan, Alysa Ziying Tan, Han Yu arxiv

We present Federated Learning Playground, an interactive browser-based platform inspired by and extends TensorFlow Playground that teaches core Federated Learning (FL) concepts. Users can experiment with heterogeneous cl…

Federated Learning

Unity RL Playground: A Versatile Reinforcement Learning Framework for Mobile Robots

2025-03-07 · Linqi Ye, Rankun Li, Xiaowen Hu, Jiayi Li 외

This paper introduces Unity RL Playground, an open-source reinforcement learning framework built on top of Unity ML-Agents. Unity RL Playground automates the process of training mobile robots to perform various locomotio…

Unity

MO-Playground: Massively Parallelized Multi-Objective Reinforcement Learning for Robotics

2026-03-10 · Neil Janwani, Ellen Novoseller, Vernon J. Lawhern, Maegan Tucker arxiv

Multi-objective reinforcement learning (MORL) is a powerful tool to learn Pareto-optimal policy families across conflicting objectives. However, unlike traditional RL algorithms, existing MORL algorithms do not effective…

Reinforcement Learning

Speech Playground: An Interactive Tool for Speech Analysis and Comparison

2026-07-01 · Stephen McIntosh, Daisuke Saito, Nobuaki Minematsu arxiv

This paper presents Speech Playground, an interactive speech visualization and comparison tool. While existing tools such as Praat are excellent, it can be cumbersome to integrate them with modern deep learning represent…

MeMemo: On-device Retrieval Augmentation for Private and Personalized Text Generation

2024-07-02 · Zijie J. Wang, Duen Horng Chau

Retrieval-augmented text generation (RAG) addresses the common limitations of large language models (LLMs), such as hallucination, by retrieving information from an updatable external knowledge base. However, existing ap…

Hallucination RAG Retrieval Text Generation