Versatile Locomotion Planning and Control for Humanoid Robots.
Versatile Locomotion Planning and Control for Humanoid Robots.
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人形机器人的多功能运动计划和控制。
DOI：
10.3389/frobt.2021.712239
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发表时间：
2021
影响因子：
3.4
通讯作者：
Sentis L
中科院分区：
文献类型：
--
作者：
Ahn J;Jorgensen SJ;Bang SH;Sentis L
我们提出了一个双足机器人的运动框架，包括一个新的运动规划方法，被称为轨迹优化的步行机器人加（TOWR+），和一个新的全身控制方法，被称为隐式分层全身控制器（IHWBC）。对于多功能性，我们考虑使用复合刚体（CRB）模型来优化机器人的行走行为。所提出的CRB模型考虑了浮动基础动力学，同时考虑了使用预训练的质心惯性网络的人形机器人的重远端质量的影响。TOWR+利用其前身TOWR的基于相位的参数化，并优化基座和末端执行器运动、脚接触扳手以及接触时间和位置，而无需解决互补问题或整数规划。IHWBC的使用强制执行单侧接触约束（即，非滑动和非穿透约束）和通过成本函数的任务层次，放松接触约束并提供任务之间的隐式层次。该控制器提供了额外的灵活性和平滑的任务和接触过渡，适用于我们的10自由度，线脚机器人DRACO。此外，我们引入了一个新的开源和轻量级的软件架构，称为规划和控制（PnC），实现并结合TOWR+和IHWBC。PnC提供了模块化、多功能性和可扩展性，因此所提供的模块可以与其他运动规划器和全身控制器互换，并以端到端的方式进行测试。在实验部分中，我们首先使用各种两足动物分析TOWR+的性能。然后，我们证明了平衡行为的DRACO硬件使用建议的IHWBC方法。最后，我们将TOWR+和IHWBC集成，并在DRACO硬件上演示步进和停止行为。
We propose a locomotion framework for bipedal robots consisting of a new motion planning method, dubbed trajectory optimization for walking robots plus (TOWR+), and a new whole-body control method, dubbed implicit hierarchical whole-body controller (IHWBC). For versatility, we consider the use of a composite rigid body (CRB) model to optimize the robot’s walking behavior. The proposed CRB model considers the floating base dynamics while accounting for the effects of the heavy distal mass of humanoids using a pre-trained centroidal inertia network. TOWR+ leverages the phase-based parameterization of its precursor, TOWR, and optimizes for base and end-effectors motions, feet contact wrenches, as well as contact timing and locations without the need to solve a complementary problem or integer program. The use of IHWBC enforces unilateral contact constraints (i.e., non-slip and non-penetration constraints) and a task hierarchy through the cost function, relaxing contact constraints and providing an implicit hierarchy between tasks. This controller provides additional flexibility and smooth task and contact transitions as applied to our 10 degree-of-freedom, line-feet biped robot DRACO. In addition, we introduce a new open-source and light-weight software architecture, dubbed planning and control (PnC), that implements and combines TOWR+ and IHWBC. PnC provides modularity, versatility, and scalability so that the provided modules can be interchanged with other motion planners and whole-body controllers and tested in an end-to-end manner. In the experimental section, we first analyze the performance of TOWR+ using various bipeds. We then demonstrate balancing behaviors on the DRACO hardware using the proposed IHWBC method. Finally, we integrate TOWR+ and IHWBC and demonstrate step-and-stop behaviors on the DRACO hardware.