RPC: A Modular Framework for Robot Planning, Control, and Deployment
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arXiv
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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866913501499359232 |
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| author | Bang, Seung Hyeon Gonzalez, Carlos Moore, Gabriel Kang, Dong Ho Seo, Mingyo Sentis, Luis |
| author_facet | Bang, Seung Hyeon Gonzalez, Carlos Moore, Gabriel Kang, Dong Ho Seo, Mingyo Sentis, Luis |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_10015 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | RPC: A Modular Framework for Robot Planning, Control, and Deployment Bang, Seung Hyeon Gonzalez, Carlos Moore, Gabriel Kang, Dong Ho Seo, Mingyo Sentis, Luis Robotics 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. |
| title | RPC: A Modular Framework for Robot Planning, Control, and Deployment |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.10015 |