In this paper, we propose a whole-body planning framework that unifies dynamic locomotion and manipulation tasks by formulating a single multi-contact optimal control problem. We model the hybrid nature of a generic multi-limbed mobile manipulator as a switched system, and introduce a set of constraints that can encode any pre-defined gait sequence or manipulation schedule in the formulation. Since the system is designed to actively manipulate its environment, the equations of motion are composed by augmenting the robot's centroidal dynamics with the manipulated-object dynamics. This allows us to describe any high-level task in the same cost/constraint function. The resulting planning framework could be solved on the robot's onboard computer in real-time within a model predictive control scheme. This is demonstrated in a set of real hardware experiments done in free-motion, such as base or end-effector pose tracking, and while pushing/pulling a heavy resistive door. Robustness against model mismatches and external disturbances is also verified during these test cases.
翻译:在本文中,我们提出一个全机规划框架,通过制定单一的多接触最佳控制问题,统一动态移动和操纵任务。我们将通用多升式移动操纵器的混合性质作为交换系统,并引入一系列限制,可以将任何预设的动作序列或操纵时间表编码成设计中的任何编程或编程。由于系统的设计是为了积极操纵环境,运动方程式的方程式是用被操纵的物体动态增强机器人的半机器人动态。这使我们能够用同样的成本/约束功能描述任何高层次任务。由此产生的规划框架可以在一个模型预测控制计划内实时在机器人机上计算机上解决。这体现在一套在自由动作中进行的实际硬件实验中,例如基础或终端效应进行跟踪,同时推动/拉动一个沉重的耐力门。在这些测试案例中,也可以核实对模型不匹配和外部扰动的强力。