RPC: A Modular Framework for Robot Planning, Control, and Deployment
Seung Hyeon Bang, Carlos Gonzalez, Gabriel Moore, Dong Ho Kang, Mingyo, Seo, and Luis Sentis

TL;DR
RPC is an open-source, modular framework that integrates simulation, planning, control, and debugging tools to facilitate development and evaluation of robotic algorithms.
Contribution
It introduces a modular, cohesive software framework that simplifies integration of various robotics components for manipulators and legged robots.
Findings
Supports multiple model-based planning and control algorithms.
Provides comprehensive debugging and operator tools.
Eases development of complex robotic tasks.
Abstract
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…
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Taxonomy
TopicsAI-based Problem Solving and Planning · Robotic Path Planning Algorithms
