外部扰动下航空机械臂的多向相互作用力控制

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Autonomous Robots Pub Date : 2023-09-01 DOI:10.1007/s10514-023-10128-2
Grzegorz Malczyk, Maximilian Brunner, Eugenio Cuniato, Marco Tognon, Roland Siegwart
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引用次数: 0

摘要

为了提高交互式空中机器人的精度和鲁棒性,了解作用在平台上的力是至关重要的。机器人应区分外力与外界干扰的相互作用,以适应前者,拒绝后者。这是一个挑战,因为干扰可能具有不同的性质(物理接触、空气动力学、建模错误),并应用于机器人的不同点。这项工作提出了一种新的基于\(\hbox {extended Kalman filter (EKF)}\)的外部干扰和相互作用力估计器。该估计器将来自系统动态模型的信息和来自力-扭矩传感器的扳手测量信息融合在一起。这允许在工具尖端进行强大的交互控制,即使存在外部干扰扳手作用于平台。我们在一种新的混合力/运动控制器中使用滤波器估计,不仅沿着工具方向,而且从任何平台的方向执行力跟踪,而不会失去姿态控制器的稳定性。所提出的框架在全向航空机械臂(AM)上进行了广泛的测试,该机械臂在受到外部干扰的情况下执行推滑操作以及在不同交互表面之间的转换。实验用两种不同的工具来装备AM:刚性相互作用杆和驱动delta机械手,显示了该方法的通用性。此外,将估计结果与最先进的基于动量的估计器进行了比较,清楚地显示了EKF方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Multi-directional Interaction Force Control with an Aerial Manipulator Under External Disturbances

To improve accuracy and robustness of interactive aerial robots, the knowledge of the forces acting on the platform is of uttermost importance. The robot should distinguish interaction forces from external disturbances in order to be compliant with the firsts and reject the seconds. This represents a challenge since disturbances might be of different nature (physical contact, aerodynamic, modeling errors) and be applied to different points of the robot. This work presents a new \(\hbox {extended Kalman filter (EKF)}\) based estimator for both external disturbance and interaction forces. The estimator fuses information coming from the system’s dynamic model and it’s state with wrench measurements coming from a Force-Torque sensor. This allows for robust interaction control at the tool’s tip even in presence of external disturbance wrenches acting on the platform. We employ the filter estimates in a novel hybrid force/motion controller to perform force tracking not only along the tool direction, but from any platform’s orientation, without losing the stability of the pose controller. The proposed framework is extensively tested on an omnidirectional aerial manipulator (AM) performing push and slide operations and transitioning between different interaction surfaces, while subject to external disturbances. The experiments are done equipping the AM with two different tools: a rigid interaction stick and an actuated delta manipulator, showing the generality of the approach. Moreover, the estimation results are compared to a state-of-the-art momentum-based estimator, clearly showing the superiority of the EKF approach.

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来源期刊
Autonomous Robots
Autonomous Robots 工程技术-机器人学
CiteScore
7.90
自引率
5.70%
发文量
46
审稿时长
3 months
期刊介绍: Autonomous Robots reports on the theory and applications of robotic systems capable of some degree of self-sufficiency. It features papers that include performance data on actual robots in the real world. Coverage includes: control of autonomous robots · real-time vision · autonomous wheeled and tracked vehicles · legged vehicles · computational architectures for autonomous systems · distributed architectures for learning, control and adaptation · studies of autonomous robot systems · sensor fusion · theory of autonomous systems · terrain mapping and recognition · self-calibration and self-repair for robots · self-reproducing intelligent structures · genetic algorithms as models for robot development. The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.
期刊最新文献
Optimal policies for autonomous navigation in strong currents using fast marching trees A concurrent learning approach to monocular vision range regulation of leader/follower systems Correction: Planning under uncertainty for safe robot exploration using gaussian process prediction Dynamic event-triggered integrated task and motion planning for process-aware source seeking Continuous planning for inertial-aided systems
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