Quasi-Static Modeling and Controlling for Planar Pushing of Deformable Objects

IF 10.5 1区 计算机科学 Q1 ROBOTICS IEEE Transactions on Robotics Pub Date : 2025-01-23 DOI:10.1109/TRO.2025.3532500
Lijun Han;Yiming Liu;Hesheng Wang
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Abstract

Pushing is an essential nonprehensile manipulation for robots to achieve complex tasks. Until now, object rigidity remains one of the common assumptions in robotic pushing. To endow robots with the advanced capability of pushing deformable objects, we propose a mathematical model and control method for the planar pushing of deformable objects. Given the robotic end-effector velocity or position input, the model predicts the motion and deformation of the pushed object, which is developed based on the quasi-static finite element analysis with reasonable simplification, considering the contact conditions of nodes with both the operator and the contact surface. By combining the designed model to estimate the state of the object and interactions with the environment, we further propose a method based on model predictive control to realize the pushing control. With a specialized simplified model to accelerate prediction, the controller is solved by iterative linear quadratic regulator with a dynamic weight, which balances the object motion and pushing area adjustment. The accuracy and efficiency of the proposed deformable model are validated by comparing the theoretical results with the experimental ones under different conditions, and the controller is verified by simulation and experiments.
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可变形物体平面推入的准静态建模与控制
推动是机器人完成复杂任务必不可少的非抓握操作。到目前为止,物体刚性仍然是机器人推动的常见假设之一。为了使机器人具有推进可变形物体的先进能力,提出了可变形物体平面推进的数学模型和控制方法。在给定机器人末端执行器速度或位置输入的情况下,在准静态有限元分析的基础上,合理简化了节点与操作者和接触面的接触条件,建立了预测被推物体运动和变形的模型。结合所设计的模型来估计对象的状态和与环境的交互,进一步提出了一种基于模型预测控制的方法来实现推送控制。为了加快预测速度,控制器采用带动态权值的迭代线性二次型调节器进行求解,该动态权值平衡了物体的运动和推动面积的调整。通过不同工况下理论与实验结果的对比,验证了所提变形模型的准确性和有效性,并通过仿真和实验验证了所提控制器的有效性。
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来源期刊
IEEE Transactions on Robotics
IEEE Transactions on Robotics 工程技术-机器人学
CiteScore
14.90
自引率
5.10%
发文量
259
审稿时长
6.0 months
期刊介绍: The IEEE Transactions on Robotics (T-RO) is dedicated to publishing fundamental papers covering all facets of robotics, drawing on interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and beyond. From industrial applications to service and personal assistants, surgical operations to space, underwater, and remote exploration, robots and intelligent machines play pivotal roles across various domains, including entertainment, safety, search and rescue, military applications, agriculture, and intelligent vehicles. Special emphasis is placed on intelligent machines and systems designed for unstructured environments, where a significant portion of the environment remains unknown and beyond direct sensing or control.
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