Despite their remarkable advancement in locomotion and manipulation, humanoid robots remain challenged by a lack of synchronized loco-manipulation control, hindering their full dynamic potential. In this work, we introduce a versatile and effective approach to controlling and generalizing dynamic locomotion and loco-manipulation on humanoid robots via a Force-and-moment-based Model Predictive Control (MPC). Specifically, we proposed a simplified rigid body dynamics (SRBD) model to take into account both humanoid and object dynamics for humanoid loco-manipulation. This linear dynamics model allows us to directly solve for ground reaction forces and moments via an MPC problem to achieve highly dynamic real-time control. Our proposed framework is highly versatile and generalizable. We introduce HECTOR (Humanoid for Enhanced ConTrol and Open-source Research) platform to demonstrate its effectiveness in hardware experiments. With the proposed framework, HECTOR can maintain exceptional balance during double-leg stance mode, even when subjected to external force disturbances to the body or foot location. In addition, it can execute 3-D dynamic walking on a variety of uneven terrains, including wet grassy surfaces, slopes, randomly placed wood slats, and stacked wood slats up to 6 cm high with the speed of 0.6 m/s. In addition, we have demonstrated dynamic humanoid loco-manipulation over uneven terrain, carrying 2.5 kg load. HECTOR simulations, along with the proposed control framework, are made available as an open-source project. (https://github.com/DRCL-USC/Hector_Simulation).

翻译：尽管人形机器人在运动与操控领域取得了显著进展，但同步全身操控控制的缺失仍制约着其动态潜能的充分发挥。本文提出了一种基于力与力矩模型预测控制（MPC）的通用高效方法，用于控制并泛化人形机器人的动态运动与全身操控行为。具体而言，我们构建了简化刚体动力学（SRBD）模型，通过融合人形机器人本体与操作对象的动力学特性，实现了全身协同操控。该线性动力学模型可通过MPC问题直接求解地面反作用力与力矩，从而达成高动态实时控制。所提出的框架具有高度通用性与可泛化性。我们基于HECTOR（面向增强控制与开源研究的人形机器人）平台开展了硬件实验验证：在双足站立模式下，即使躯干或足部受到外部力扰动，HECTOR仍能保持卓越平衡；它还能在多种非平坦地形（包括潮湿草地、斜坡、随机放置的木条以及最高6厘米的堆叠木条）上以0.6米/秒的速度执行三维动态行走。此外，我们还展示了其在非平坦地形上携带2.5千克载荷的动态全身操控能力。HECTOR仿真平台及配套控制框架已作为开源项目发布（https://github.com/DRCL-USC/Hector_Simulation）。