Article
Computer Science, Artificial Intelligence
Qingxin Meng, Xuzhi Lai, Ze Yan, Chun-Yi Su, Min Wu
Summary: This article discusses an uncertain two-link rigid-flexible manipulator with vibration amplitude constraint, and aims to achieve its position control through motion planning and adaptive tracking approach. The motion trajectories planning for the manipulator's two links can guarantee reaching desired angles and suppress vibration, while the adaptive tracking controller enables the two links to track the planned trajectories under various uncertainties. Simulation results confirm the effectiveness of the proposed control strategy and the superior performance of motion planning and tracking controller.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Engineering, Mechanical
Jun Li, Haibo Gao, Yuhui Wan, Joseph Humphreys, Christopher Peers, Haitao Yu, Chengxu Zhou
Summary: This paper presents an inverse dynamics-based whole-body controller that can handle locomotion and manipulation tasks simultaneously, considering the coupling effects between them. By using a hierarchical optimization algorithm to track the desired task-space motion, the robot is able to follow multiple tasks successfully.
Article
Computer Science, Artificial Intelligence
Yuchuang Tong, Jinguo Liu, Xin Zhang, Zhaojie Ju
Summary: A novel four-criterion-optimization coordination motion scheme (FCOCM) is proposed in this article to address the coordination constraints and physical constraints faced by dual-arm robots simultaneously. The scheme combines four optimization criteria and improves motion efficiency, safety, and accuracy in task execution. It also considers real-time trajectory feedback, satisfies physical constraints, and ensures zero joint angular velocity at the end of tasks. Additionally, a novel power-exponent-type variable-parameter recurrent neural network (PET-VPNN) model and Sinh-tunable type activation function are proposed for solving the improved FCOCM scheme. Simulations and experiments confirm the superiority of the proposed coordination motion control method. This research is highly significant for complex path planning tasks involving dual-arm robots.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Mincheul Kang, Sung-Eui Yoon
Summary: This paper presents a trajectory optimization method for a redundant manipulator, which can achieve smooth and collision-free manipulation while maintaining accuracy. The method integrates the Jacobian-based inverse kinematics solving method and an optimization-based motion planning approach.
Article
Engineering, Electrical & Electronic
Thushara Sandakalum, Marcelo H. Ang
Summary: This article systematically reviews the different planning algorithms used for mobile manipulator motion planning. The algorithms are categorized into two broad groups based on how they treat the two subsystems during planning. The article dissects and discusses the planning algorithms based on common components, and analyzes the challenge of dealing with kinematic redundancy. The coordination between the mobile base and manipulator, utilizing their unique capabilities, provides better solution paths.
Article
Automation & Control Systems
Naijing Jiang, Shu Zhang, Jian Xu, Dan Zhang
Summary: A model-free controller is proposed to suppress residual vibration by releasing potential energy in a sequence with two steps. The controller is simple and effective, as tested in experimental and simulation studies.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2021)
Article
Chemistry, Analytical
Taehyeon Kim, Myunghyun Kim, Sungwoo Yang, Donghan Kim
Summary: This paper proposes a simultaneous controller that can be universally applied to various types of mobile manipulator robots, with features including motion planning, obstacle avoidance, and manipulation task execution. Experimental results in both simulation and real-world environments demonstrate significant improvements and successful application of the controller in different types of robots.
Article
Computer Science, Artificial Intelligence
Yuchuang Tong, Jinguo Liu
Summary: The paper proposed a novel PET-MRNN model and Sbp-sinh type activation function to address noise and physical constraints in repetitive motion planning problems. Theoretical analysis showed the superiority of the PET-MRNN model, which was further validated through simulations and experiments.
Article
Chemistry, Analytical
Hanlin Chen, Xizhe Zang, Yubin Liu, Xuehe Zhang, Jie Zhao
Summary: This paper proposes a hierarchical motion planner for mobile manipulators, allowing autonomous configuration changes in real time. It utilizes an optimized A* algorithm for global planning of the mobile base and a sampling-based heuristic algorithm for collision-free configuration search of the manipulator. Experimental results show that the proposed method outperforms traditional methods in terms of computation time, success rate, and configuration quality.
Article
Computer Science, Artificial Intelligence
Teng Long, En Li, Yunqing Hu, Lei Yang, Junfeng Fan, Zize Liang, Rui Guo
Summary: This article introduces a combined control method for improving the tip positioning accuracy and trajectory tracking accuracy of a hybrid-structured flexible manipulator by integrating a main controller and an auxiliary controller. Experimental results validate the effectiveness and robustness of this method.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Chemistry, Multidisciplinary
Arturo Gil Aparicio, Jaime Valls Miro
Summary: This paper proposes a novel stochastic method to track end-effector task-space motion in an efficient manner by improving manipulability measure and motion planning, enhancing robot performance in the presence of obstacles.
APPLIED SCIENCES-BASEL
(2021)
Article
Robotics
Ariyan M. Kabir, Shantanu Thakar, Rishi K. Malhan, Aniruddha Shembekar, Brual C. Shah, Satyandra K. Gupta
Summary: This article presents an approach to generate path-constrained synchronous motion for a coupled ensemble of robots, addressing relative motion constraints among objects in the environment through non-linear optimization. The method formulates the problem as a discrete parameter optimization problem and solves it using successive constraint refinement techniques, adapting to different scenarios and reducing computation time. The effectiveness of the proposed method is demonstrated on challenging test cases with high-degree-of-freedom robotic systems in simulation and physical environments.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2021)
Article
Robotics
Mehdi Shahabi, Hashem Ghariblu, Manuel Beschi
Summary: The main objective of this study is to find an efficient collision-free motion planning method by evaluating and comparing different sample-based motion planning algorithms. Taking the welding of pipes as an example, the displacement path planning of the robot is considered, and multiple criteria are used to evaluate the efficiency of the algorithms.
Article
Engineering, Marine
Dongyang Shang, Xiaopeng Li, Meng Yin, Sainan Zhou
Summary: The flexible single-link underwater manipulator (FSLUM) can perform various underwater tasks in autonomous underwater vehicles, playing a significant role in ocean exploration and development. This study proposes an improved sliding mode control strategy based on neural network identification to enhance the control accuracy of the FSLUM. Simulation and prototype tracking control experiments demonstrate that the proposed strategy achieves high tracking accuracy.
Article
Automation & Control Systems
Haisen Guo, Zhigang Ren, Jialun Lai, Zongze Wu, Shengli Xie
Summary: In this paper, the problem of real-time navigation and obstacle avoidance for automated guided vehicles (AGVs) in dynamic environments is addressed. An improved Soft Actor-Critic (SAC)-based reinforcement learning methodology is proposed to overcome the computational inefficiency of recalculating optimal paths every time. The methodology utilizes a novel composite auxiliary reward structure and sum-tree prioritized experience replay (SAC-SP) to achieve real-time optimal feedback control.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Mechanics
L. Malgaca, H. Dogan, M. Akdag, S. Yavuz, M. Uyar, B. Bidikli
COMPOSITE STRUCTURES
(2018)
Article
Engineering, Mechanical
M. Uyar
Summary: This study investigates the effect of two different motion profiles on the vibration of a flexible composite manipulator. The dynamic performance is explored using theoretical and experimental approaches. The study presents a SimMechanics-based flexible dynamic model and a finite element model, and evaluates the effectiveness of the motion profiles in reducing vibration amplitudes. The results are verified through simulations and experiments, increasing the reliability of the proposed method.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2022)
Article
Engineering, Civil
Mehmet Uyar, Mustafa Ergun
Summary: This paper presents the pure active control performance of a tall building under the influence of earthquake records. The effects of single and multi-feedback controllers on vibration elimination at the top and all floors are studied. The results show that multi-feedback control is more effective than single-feedback control in reducing vibration amplitudes at all floors in the pure active control system.
Article
Automation & Control Systems
Sefika Lok, Levent Malgaca, Mehmet Uyar
Summary: This study focuses on active vibration control for a single-link composite box manipulator using a single actuator. Model extraction and system identification techniques are used to obtain mathematical models. Proportional derivative and positive position feedback controllers are implemented to reduce residual vibrations. The simulation results are verified by experiments and evaluated with reduction rates.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING
(2023)
Article
Multidisciplinary Sciences
M. Uyar
Summary: The piezoelectric energy harvesting performances of smart wind blades and smart drone propellers using lead zirconate titanate (PZT) material were evaluated. The energy harvesting performance of the smart wind blades was influenced by the blade angles, while the performance of the smart drone propellers depended on the sensor responses and polarization directions. The maximum and minimum power outputs obtained were approximately 0.086 W and 0.008 W, respectively. The results indicated that the z-polarized smart propeller had better energy harvesting performance than the y polarization, and the amount of energy obtained increased with the rotation speed and endpoint vibration amplitudes.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Multidisciplinary Sciences
M. Uyar, L. Malgaca
Summary: This study proposes a model extraction approach for vibration suppression of single-link flexible smart and composite manipulators and investigates active and passive control of residual vibrations. The optimization of control gains successfully reduces residual vibrations of smart manipulators.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
L. Malgaca, M. Uyar
COMPOSITES PART B-ENGINEERING
(2019)
