RoMoCo统一了双足机器人运动控制的高效设计与测试流程。
RoMoCo: Robotic Motion Control Toolbox for Reduced-Order Model-Based Locomotion on Bipedal and Humanoid Robots
- 基于简化模型构建模块化控制工具箱，支持快速原型设计。
- 在Cassie、H1、G1等机器人上验证，仿真与实机均表现稳定。
- 开源开放，适合研究者与工程师加速机器人步态开发。
我们提出RoMoCo，一个开源的C++工具箱，用于合成与评估基于简化模型的双足及人形机器人步态规划器和全身体控器。其模块化架构通过统一的API整合了最先进的规划算法与全身运动控制方法，支持快速原型开发与可复现的基准测试。借助简化模型实现跨平台的步态生成，使控制器设计在多种机器人平台上灵活适配。我们在Cassie、Unitree H1和G1机器人上进行了广泛的仿真验证，并在Cassie与G1人形机器人上完成了真实硬件实验，证明了该工具箱的通用性与实际有效性。
原文摘要 · Abstract (English)
We present RoMoCo, an open-source C++ toolbox for the synthesis and evaluation of reduced-order model-based planners and whole-body controllers for bipedal and humanoid robots. RoMoCo's modular architecture unifies state-of-the-art planners and whole-body locomotion controllers under a consistent API, enabling rapid prototyping and reproducible benchmarking. By leveraging reduced-order models for platform-agnostic gait generation, RoMoCo enables flexible controller design across diverse robots. We demonstrate its versatility and performance through extensive simulations on the Cassie, Unitree H1, and G1 robots, and validate its real-world efficacy with hardware experiments on the Cassie and G1 humanoids.
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