RPC整合机器人规划、控制与部署工具，支持模块化扩展。
RPC: A Modular Framework for Robot Planning, Control, and Deployment
- 模块化设计，各组件可独立替换或集成
- 支持机械臂与腿式机器人的多种模型算法
- 适合机器人算法开发与复杂任务调试
本文提出一个开源、轻量但全面的软件框架RPC，集成物理仿真器、规划控制库、调试工具和用户友好的操作界面。该框架支持对机器人系统进行完整控制算法的评估与开发。现有框架虽具备部分功能，但整合成统一系统常面临困难。为此，我们对RPC中各组件进行模块化设计，实现组件间无缝替换与集成。当前框架支持多种基于模型的规划与控制算法，适用于机械臂和腿式机器人，并配备关键调试工具，显著简化复杂机器人任务的设计与执行。代码及使用说明已公开于https://github.com/shbang91/rpc。
原文摘要 · Abstract (English)
This paper presents an open-source, lightweight, yet comprehensive software framework, named RPC, which integrates physics-based simulators, planning and control libraries, debugging tools, and a user-friendly operator interface. RPC enables users to thoroughly evaluate and develop control algorithms for robotic systems. While existing software frameworks provide some of these capabilities, integrating them into a cohesive system can be challenging and cumbersome. To overcome this challenge, we have modularized each component in RPC to ensure easy and seamless integration or replacement with new modules. Additionally, our framework currently supports a variety of model-based planning and control algorithms for robotic manipulators and legged robots, alongside essential debugging tools, making it easier for users to design and execute complex robotics tasks. The code and usage instructions of RPC are available at https://github.com/shbang91/rpc.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。