5分钟完成机器人纳管、10秒启动跨集群任务,清华大学联合无问芯穹开源具身智能云原生平台RLark
AI 导读
具身智能云原生平台跨集群通信优化开源协作任务级编排资源调度复用
清华大学联合无问芯穹开源具身智能云原生平台RLark,通过统一设备管理、跨集群通信优化和任务级编排,实现机器人纳管5分钟、任务启动10秒,为大规模具身智能实验提供基础设施支持。
Tsinghua University and Wuxian Xinqiong open-source RLark, a cloud-native platform for embodied intelligence, achieving 5-minute device management and 10-second task startup through unified orchestration and cross-cluster communication optimization.
重点速览
- 统一管理机器人、相机等设备资源,实现云边端资源调度复用 Unified management of robots, cameras, and edge devices for cloud-edge resource scheduling
- 任务级跨集群通信优化,提升大包传输吞吐量49% Task-level cross-cluster communication optimization boosts large packet throughput by 49%
- 开源降低基础设施门槛,支持跨地域实验闭环 Open-source lowers infrastructure barriers for cross-regional experiments
- 自研具身运行时将设备转化为可调度资源 Custom embodied runtime converts physical devices into schedulable resources
- 控制面+数据面架构实现任务全链路观测 Control plane + data plane architecture enables end-to-end task observability
一句话:RLark通过云原生架构重构具身智能基础设施,实现复杂任务的高效协同与规模化部署。 / RLark redefines embodied intelligence infrastructure with cloud-native architecture, enabling efficient collaboration and scalable deployment of complex tasks.
推荐理由 该技术突破解决了具身智能规模化部署的核心痛点,为跨地域协同实验提供可复用的基础设施范式。
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