Purpose

Admittance control is a typical complaint control methodology. Traditionally, admittance control systems are based on a dynamical relationship described by Voigt model. By contrast, after changing connection of spring and damper, Maxwell model produces different dynamics and has shown better impact absorption performance. This paper aims to design a novel compliant control method based on Maxwell model and implement it in a robot catching scenario.

Design/methodology/approach

To achieve this goal, this paper proposed a Maxwell model based admittance control scheme. Considering several motion stages involved in one catching attempt, the following approaches are adopted. First, Kalman filter is used to process the position data stream acquired from motion capture system and predict the subsequent object flying trajectory. Then, a linear segments with parabolic blends reaching motion is generated to achieve time-optimal movement under kinematic and joint inherent constraints. After robot reached the desired catching point, the proposed Maxwell model based admittance controller performs such as a cushion to moderate the impact between robot end-effector and flying object.

Findings

This paper has experimentally demonstrated the feasibility and effectiveness of the proposed method. Compared with typical Voigt model based compliant catching, less object bounding away from end-effector happens and the success rate of catching has been improved.

Originality/value

The authors proposed a novel Maxwell model based admittance control method and demonstrated its effectiveness in a robot catching scenario. The author’s approach may inspire other related researchers and has great potential of practical usage in a widespread of robot applications.

中文翻译：

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基于麦克斯韦模型的笛卡尔导纳控制的机器人兼容捕捉

目的

准入控制是一种典型的投诉控制方法。传统上，导纳控制系统基于 Voigt 模型描述的动态关系。相比之下，改变弹簧和阻尼器的连接后，麦克斯韦模型产生不同的动力学，表现出更好的冲击吸收性能。本文旨在设计一种基于麦克斯韦模型的新型柔性控制方法，并在机器人捕捉场景中实现。

设计/方法/方法

为了实现这一目标，本文提出了一种基于麦克斯韦模型的导纳控制方案。考虑到一次捕捉尝试涉及多个运动阶段，采用以下方法。首先，卡尔曼滤波器用于处理从运动捕捉系统获取的位置数据流，并预测后续物体的飞行轨迹。然后，生成具有抛物线混合到达运动的线性段，以在运动学和关节固有约束下实现时间最优运动。机器人到达所需的捕捉点后，基于麦克斯韦模型的导纳控制器执行缓冲等操作，以减轻机器人末端执行器与飞行物体之间的冲击。

发现

本文通过实验证明了所提出方法的可行性和有效性。与典型的基于Voigt模型的顺应捕捉相比，远离末端执行器的物体边界发生的情况更少，捕捉的成功率得到了提高。

原创性/价值

作者提出了一种新的基于 Maxwell 模型的导纳控制方法，并证明了其在机器人捕捉场景中的有效性。作者的方法可能会启发其他相关研究人员，并且在广泛的机器人应用中具有巨大的实际应用潜力。