Article
Robotics
Bohan Yang, Bo Lu, Wei Chen, Fangxun Zhong, Yun-Hui Liu
Summary: This article proposes a model-free controller using novel 3-D global deformation features based on modal analysis for shape control of deformable objects. The controller employs physically based deformation features designed by decoupling global deformation into low-frequency modes. A new model-free framework for modal-based deformation control is developed, which formulates an analytical deformation Jacobian matrix mapping the robot manipulation onto changes of the modal features. Simulations and experiments demonstrate the superior performance and advantages of the controller over the baseline method.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Engineering, Civil
Huimin Lu, Yadong Teng, Yujie Li
Summary: In recent years, the methods of loading and transporting rigid objects have improved. However, controlling the shape of deformable objects during transportation has attracted attention. This study uses contrastive learning to solve the shape control problem of deformable objects and improves the model's representation ability by constructing an encoder to extract effective information. Experimental results show significant performance improvements compared to baseline methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Automation & Control Systems
Lijun Han, Hesheng Wang, Zhe Liu, Weidong Chen, Xiufeng Zhang
Summary: This article proposes a method to control the trajectory of deformation in an unknown environment. An adaptive dynamic controller is designed to estimate the deformation Jacobian matrix based on function approximation techniques, and a virtual force is introduced to improve manipulability.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Steeve Mbakop, Gilles Tagne, Sergey Drakunov, Rochdi Merzouki
Summary: Mobile soft continuum manipulator (MSCM) is widely used in various applications of everyday life. However, its shape control in unstructured environments remains a challenge. This paper proposes a kinematic-model-based shape control method for MSCM's autonomous navigation in the presence of obstacles. The shape is modeled using a parametric spatial Pythagorean hodograph (PH) curve, and the artificial potential field algorithm is used for shape adaptation. Experimental results demonstrate the advantages of using a simplified kinematic model based on PH curve for controlling the MSCM's shape in dynamic motion.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Robotics
Mingrui Yu, Kangchen Lv, Hanzhong Zhong, Shiji Song, Xiang Li
Summary: This paper proposes a coupled offline and online data-driven method for learning the global deformation model of DLOs. By training offline and updating online, the method can efficiently and accurately estimate the deformation model and achieve large deformation control.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Engineering, Mechanical
Haobin Xue, Jie Huang
Summary: This article presents a dynamic model and control method for underwater soft-link manipulators, and analyzes the frequencies and mode shapes of the liquid-link interaction. Simulated and experimental results validate the utility of the model and method.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Automation & Control Systems
B. Melih Yilmaz, Enver Tatlicioglu, Aydogan Savran, Musa Alci
Summary: The main objective of this article is to study the end effector tracking control of robot manipulators subject to dynamical uncertainties. Direct task space control is preferred to minimize the end effector tracking error directly, and a self-adjusting adaptive fuzzy logic component is designed as part of the control input torque. The viability of the proposed control strategy is demonstrated with experimental results, and extensions to the cases of uncertain Jacobian and kinematically redundant robots are presented.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Optics
Aleksandar Haber, Thomas Bifano
Summary: The developed method adaptively determines a DM model and control actions through an iterative process, achieving precise control of deformable mirrors. Experimental results demonstrate that this method can achieve accurate correction within a few control iterations.
Article
Automation & Control Systems
Jiazheng Zhang, Long Jin, Chenguang Yang
Summary: In this article, a multimanipulator cooperative control scheme with improved communication efficiency is proposed. The scheme formulates the entire control process from the perspective of game theory and uses a neural network solver to update the strategies of manipulators. Theoretical analysis and simulation results support the superiority of the proposed control strategy.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Wei Zhao, Yu Liu, Xiangqian Yao
Summary: This article investigates the cooperative vibration control problem for a flexible manipulator network with model uncertainties and boundary disturbances guided by multiple dynamic leaders. The article proposes a boundary control algorithm for leader agents without disturbance and follower agents with disturbance and uncertainties using fuzzy logic systems. The control method aims to suppress vibrations and converge the containment error between the leaders and followers to zero. Simulation results demonstrate the effectiveness of the proposed control method.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Robotics
Yichen Huang, Chongkun Xia, Xueqian Wang, Bin Liang
Summary: This letter focuses on the shape control manipulation of deformable linear objects (DLO) with a dual-arm robotic system. One significant challenge of DLO shape control is the underactuated control system, which means that finite robotic manipulators can not fully control DLO's shape due to the lack of sufficient constraints on DLO. We propose a novel DLO shape control framework aiming to stably control DLO's shape in a wide deformation range, which innovatively provides additional constraints on DLO via external contact.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Automation & Control Systems
Seungyeon Kim, Taegyun Ahn, Yonghyeon Lee, Jihwan Kim, Michael Yu Wang, Frank C. Park
Summary: This paper proposes a two-step method that combines deformable superquadrics with a deep learning network to identify and grasp partially occluded objects. Experimental results show improved success rates and faster recognition compared to existing methods.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Robotics
Zhenxi Cui, Wanyu Ma, Jiewen Lai, Henry K. Chu, Yi Guo
Summary: This letter introduces an adaptive term to solve the generalization problem of coupled multiple DMPs and model deformable objects. Based on this method, the manipulation of deformable objects can be treated as a second-order system, providing greater flexibility and robustness. Simulation and experimental results demonstrate the effectiveness of this approach.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Automation & Control Systems
Jialiang Fan, Long Jin, Zhengtai Xie, Shuai Li, Yu Zheng
Summary: This article proposes a new data-driven motion-force control scheme to address the problem of redundant manipulator control. The scheme uses a recurrent neural network to estimate the structure information and demonstrates excellent performance and practicality.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Zhengtai Xie, Long Jin, Xin Luo, Shuai Li, Xiuchun Xiao
Summary: This article introduces a data-driven cyclic-motion generation (CMG) scheme and a novel dynamic neural network (DNN) approach to precisely control redundant manipulators with unknown models, effectively eliminating tracking errors. The proposed method demonstrates strong learning and control abilities, proving its reliability and superior performance through computer simulation results and comparisons.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2021)
Article
Robotics
Aime Charles Alfred Dione, Shoichi Hasegawa
Summary: This study proposes a new method to solve the kinematic hyper redundancy problem in posture control of a robotic arm with redundant degrees of freedom. By controlling strategic points along the arm, the method guides the overall motion of the arm towards the target posture. The method is capable of safely and accurately tracking target postures that are significantly different from the initial posture.
Article
Robotics
Peirang Li, Naoya Ueda, Chi Zhu
Summary: This study focuses on the traditional attendant-propelled power-assist wheelchairs (APAWs) and identifies the discomfort caused by changes in handle velocity when passing through a slope. To address this issue, a velocity compensation method is proposed and validated through simulations and experiments.
Article
Robotics
Juan Padron, Kenta Tatsuda, Kiyoshi Ohishi, Yuki Yokokura, Toshimasa Miyazaki
Summary: This paper proposes a method that takes into account real-time posture-dependent inertial variation to achieve exact dynamic compensation and independent control of each axis for industrial robots. By discretizing the state equations of the posture-variant two-inertia system model, the whole control system can be easily redeisgned at each control cycle to address the issues caused by posture changes.
