State-of-the-art approaches to footstep planning assume reduced-order dynamics when solving the combinatorial problem of selecting contact surfaces in real time. However, in exchange for computational efficiency, these approaches ignore joint torque limits and limb dynamics. In this work, we address these limitations by presenting a topology-based approach that enables~\gls{mpc} to simultaneously plan full-body motions, torque commands, footstep placements, and contact surfaces in real time. To determine if a robot's foot is inside a contact surface, we borrow the winding number concept from topology. We then use this winding number and potential field to create a contact-surface penalty function. By using this penalty function,~\gls{mpc} can select a contact surface from all candidate surfaces in the vicinity and determine footstep placements within it. We demonstrate the benefits of our approach by showing the impact of considering full-body dynamics, which includes joint torque limits and limb dynamics, on the selection of footstep placements and contact surfaces. Furthermore, we validate the feasibility of deploying our topology-based approach in an~\gls{mpc} scheme and explore its potential capabilities through a series of experimental and simulation trials.
翻译:现有的足步规划方法在实时选择接触表面时,假定采用降阶动力学。然而为了获得计算效率,这些方法忽略了关节力矩限制和肢体动力学。本研究通过提出一种基于拓扑学的方法,使得模型预测控制能够以实时方式同时规划全身动作、扭矩控制、足底位置和接触表面。为了确定机器人足部是否位于接触表面内部,我们采用了拓扑学中的绕数概念。然后,我们利用绕数和势能场划分出一种接触表面惩罚函数。通过使用该函数,模型预测控制可以从周围所有候选表面中选择接触表面以及在该表面内确定足底位置。我们通过展示全身动力学的影响,包括关节力矩限制和肢体动力学,来证明我们的方法的优势。此外,我们通过一系列实验和模拟试验验证了部署我们基于拓扑学方法的模型预测控制的可行性,并探索了它的潜在能力。