Optimization-Based Control for Dynamic Legged Robots
Optimization-Based Control for Dynamic Legged Robots
复制标题
基于优化的动态腿式机器人控制
DOI：
10.1109/tro.2023.3324580
复制
发表时间：
2022-11
影响因子：
7.8
通讯作者：
Patrick M. Wensing;Michael Posa;Yue Hu;Adrien Escande;N. Mansard;A. Prete
中科院分区：
文献类型：
--
作者：
Patrick M. Wensing;Michael Posa;Yue Hu;Adrien Escande;N. Mansard;A. Prete
在一个为腿而设计的世界里，四足动物、两足动物和人形机器人有机会影响从物流到农业再到家庭援助的新兴机器人应用。这项调查的目标是涵盖这些应用程序的最新进展，这些应用程序是由基于模型的优化驱动的，用于实时生成和控制运动。大多数研究界都集中在通过以基于模型或数据驱动的方式解决最优控制问题(OCP)来生成运动控制律的想法。然而，由于与环境的间歇性单向接触以及腿部机器人的许多自由度的复杂性，在线解决这些最普遍的问题仍然是困难的。这项调查涵盖了使这些OCP易于计算的方法，特别关注如何处理环境接触，如何简化模型，以及这些选择如何影响所采用的数值解方法。调查的重点是基于模型的优化，同时为更广泛地与基于学习的配方相结合铺平道路，以加快这一不断增长的领域的进展。
In a world designed for legs, quadrupeds, bipeds, and humanoids have the opportunity to impact emerging robotics applications from logistics, to agriculture, to home assistance. The goal of this survey is to cover the recent progress toward these applications that have been driven by model-based optimization for the real-time generation and control of movement. The majority of the research community has converged on the idea of generating locomotion control laws by solving an optimal control problem (OCP) in either a model-based or data-driven manner. However, solving the most general of these problems online remains intractable due to complexities from intermittent unidirectional contacts with the environment, and from the many degrees of freedom of legged robots. This survey covers methods that have been pursued to make these OCPs computationally tractable, with a specific focus on how environmental contacts are treated, how the model can be simplified, and how these choices affect the numerical solution methods employed. The survey focuses on model-based optimization while paving its way for broader combination with learning-based formulations to accelerate progress in this growing field.