论文标题

使用被动任务空间控制器的叠加对冗余机器人的安全和兼容控制

Safe and Compliant Control of Redundant Robots Using Superimposition of Passive Task-Space Controllers

论文作者

Tiseo, Carlo, Merkt, Wolfgang, Wolfslag, Wouter, Vijayakumar, Sethu, Mistry, Michael

论文摘要

在与环境相互作用时,对动态系统的安全和兼容控制,例如在共享工作区中,继续代表了一个重大挑战。机器人的动态模型,数值奇点和内在环境不可预测性的不匹配都是促成因素。在线优化阻抗控制器最近在应对这一挑战方面表现出了巨大的希望,但是,它们的性能不足以在具有挑战性的环境中部署。这项工作提出了一种基于层次结构中多个被动任务空间控制器的叠加的冗余操纵器的合规控制方法。我们的被动控制器的控制框架本质上是稳定的,数值良好的条件(由于不需要矩阵倒置),并且计算便宜(由于不使用优化)。我们利用并引入了一个新型的刚度曲线,为最近提出的一个被动控制器,在散发和收敛阶段之间平滑过渡,从而在通过叠加组合组合多个被动控制器时特别适合。我们的实验结果表明,所提出的方法在苛刻的动态任务期间以快速变化的参考进行了次级跟踪性能,同时保持安全互动并与奇异性相互作用。他提出的框架在不了解机器人动态的情况下实现了这种结果,并且由于其被动性本质上是稳定的。数据进一步表明,机器人可以充分利用冗余,以维持主要任务准确性,同时补偿未知的环境互动,这是从需要准确的接触信息的当前框架中不可能的。

Safe and compliant control of dynamic systems in interaction with the environment, e.g., in shared workspaces, continues to represent a major challenge. Mismatches in the dynamic model of the robots, numerical singularities, and the intrinsic environmental unpredictability are all contributing factors. Online optimization of impedance controllers has recently shown great promise in addressing this challenge, however, their performance is not sufficiently robust to be deployed in challenging environments. This work proposes a compliant control method for redundant manipulators based on a superimposition of multiple passive task-space controllers in a hierarchy. Our control framework of passive controllers is inherently stable, numerically well-conditioned (as no matrix inversions are required), and computationally inexpensive (as no optimization is used). We leverage and introduce a novel stiffness profile for a recently proposed passive controller with smooth transitions between the divergence and convergence phases making it particularly suitable when multiple passive controllers are combined through superimposition. Our experimental results demonstrate that the proposed method achieves sub-centimeter tracking performance during demanding dynamic tasks with fast-changing references, while remaining safe to interact with and robust to singularities. he proposed framework achieves such results without knowledge of the robot dynamics and thanks to its passivity is intrinsically stable. The data further show that the robot can fully take advantage of the redundancy to maintain the primary task accuracy while compensating for unknown environmental interactions, which is not possible from current frameworks that require accurate contact information.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源