Article
Robotics
Xing Zhou, Yaoqi Xian, Yuanhao Chen, Tongshu Chen, Lin Yang, Simin Chen, Jian Huang
Summary: This paper proposes an improved method for solving the inverse kinematics problem of 6-DOF robot manipulators with offset wrists. The method utilizes the Newton iteration technique and does not require the selection of initial estimates for joint variables. The solution is divided into two parts: an analytical solution for a simplified structure and a numerical solution obtained through iteration. The method is demonstrated on a robot manipulator HSR-BR606 with an offset wrist, showing higher accuracy and shorter calculation time compared to a typical IK algorithm.
Article
Computer Science, Information Systems
David Feller
Summary: This article presents the solution to the inverse and forward kinematics of a novel robot design that combines serial and parallel architecture. The solution is derived using spherical trigonometry and spatial vector geometry and provides a unique and efficient solution. The derived robot kinematics are verified through a 3D simulation model.
Article
Automation & Control Systems
Chengshi Wang, Chase G. Frazelle, John R. Wagner, Ian D. Walker
Summary: This article presents a novel control strategy for trajectory control of multisection continuum robots in three-dimensional space. By connecting the dynamic behavior of the continuum manipulator to a virtual discrete-jointed robot, a computed torque control architecture is developed, resulting in improved performance during various maneuvers.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2021)
Article
Mathematics
Carlos Lopez-Franco, Dario Diaz, Jesus Hernandez-Barragan, Nancy Arana-Daniel, Michel Lopez-Franco
Summary: In this paper, a general method using metaheuristic optimization methods is proposed to solve the trajectory tracking problem of robot manipulators. The method can be applied to robots with any number of degrees of freedom (DOF) to find the optimal joint configuration for minimizing the position and orientation of the end-effector in 3D.
Article
Engineering, Electrical & Electronic
Minghao Li, Xiao Luo, Lijun Qiao
Summary: In this paper, a novel BODE-CS algorithm is presented to solve the inverse kinematics problem of a six-DOF EOD robot manipulator. The algorithm combines the differential evolution and cuckoo search algorithms to avoid local optima and achieve fast convergence. Experimental results show that the BODE-CS algorithm has high accuracy and a fast convergence rate, meeting the requirements of the inverse solution for the manipulator.
Article
Engineering, Electrical & Electronic
Pavel Laryushkin, Anton Antonov, Alexey Fomin, Terence Essomba
Summary: This article presents the velocity and singularity analysis for a five-degree-of-freedom (5-DOF) parallel-serial manipulator. The study discusses the manipulator design and the results of the position analysis, and then performs velocity and singularity analysis using screw theory. The article also investigates singular configurations and presents conditions for serial and parallel singularities.
Article
Automation & Control Systems
Paul Milenkovic
Summary: Adjusting the displacement path of a serial robot encountering the wrist singularity to pass through or around it can mitigate adverse effects and avoid high joint rates. Recent methods limiting joint rates and accelerations in robot traversal while maintaining accurate tool position are beneficial. Choosing between through and around-singularity alternatives provides overall optimal results.
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME
(2021)
Article
Engineering, Electrical & Electronic
Vadim Kramar, Oleg Kramar, Aleksey Kabanov
Summary: The paper proposes a new design of an artificial neural network to solve the inverse kinematics problem of a robot manipulator. By using elements from a homogeneous transformation matrix obtained based on the Denavi-Hartenberg notation, the accuracy of the neural network is improved. Additionally, by adding a correctional neural network, the accuracy can be increased twofold.
Article
Engineering, Aerospace
Xiaohang Yang, Zhiyuan Zhao, Zichun Xu, Yuntao Li, Jingdong Zhao, Hong Liu
Summary: This paper presents a general numerical methodology for inverse kinematics computation of 7-degree-of-freedom offset manipulators based on arm angle parameterization. It derives analytical inverse kinematics solutions for two types of Spherical-Revolute-Spherical manipulators using arm angle parameterization. The inverse kinematics of the offset manipulator is solved using a simplified manipulator, where the error between the actual manipulator and desired position is utilized to gradually improve the inverse solution of the simplified manipulator.
Article
Chemistry, Multidisciplinary
Hasan Danaci, Luong A. Nguyen, Thomas L. Harman, Miguel Pagan
Summary: Inverse kinematics is a fundamental problem in manipulator robotics. Traditional solution techniques include analytical kinematics solvers and numerical methods. Recent swarm intelligence technology has also contributed to manipulator inverse kinematics solutions.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Mechanical
Boyu Ma, Zongwu Xie, Zainan Jiang, Hong Liu
Summary: This study proposes a high-precision, semi-analytical inverse method for seven-degree-of-freedom redundant manipulators with link offset, addressing the difficulty of finding analytical solutions based on arm angle parameterization for the experimental module manipulator.
FRONTIERS OF MECHANICAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Shiqi Li, Ke Han, Ping He, Zhuo Li, Yizhang Liu, Youjun Xiong
Summary: This paper presents an integrated scheme for solving the path-wise inverse kinematics problem of a 7-DoF anthropomorphic manipulator with radial elbow offset. The scheme focuses on achieving natural arm configurations and human-like behavior in human-centered environments. An analytical inverse kinematics solution is derived based on arm angle parameterization, and a natural arm configuration mapped to wrist position is proposed. A LSTM-based natural arm angle prediction network is designed and trained, and a redundancy resolution framework is built for generating smooth and natural joint configurations. Comparative experiments show the efficiency and precision of the proposed analytical IK algorithm, and path tracking experiments validate the effectiveness and anthropomorphism of the redundancy resolution scheme based on the trained network.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Heng Deng, Chong Xie
Summary: The study proposes an inverse kinematic solution based on an adaptive fitness function and particle swarm optimization algorithm, which efficiently and accurately solves the kinematic problem of multi-DOF manipulators.
Article
Robotics
Zhihong Zou
Summary: This article proposes a methodology of using manipulability polytopes to characterize the manipulator's capability and presents a systematic architecture and detailed procedures for performance computation. The proposed methodology has been validated through two application examples.
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Ying Sun, Leyuan Mi, Du Jiang, Xiaofeng Zhang, Juntong Yun, Ying Liu, Li Huang, Bo Tao, Zifan Fang
Summary: In this study, a novel solution to the inverse kinematics problem (IKP) for non-spherical robots is proposed. The method transforms the IKP into an optimization problem and introduces a new objective function based on geometric characteristics. It utilizes the adaptive covariance matrix evolution strategy (CMA-ES) and an analytical method to achieve precise solutions.
Article
Computer Science, Interdisciplinary Applications
Metin Toz, Serdar Kucuk
COMPUTER APPLICATIONS IN ENGINEERING EDUCATION
(2015)
Article
Computer Science, Artificial Intelligence
Metin Toz, Serdar Kucuk
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
(2016)
Article
Robotics
Metin Toz, Serdar Kucuk
Article
Computer Science, Interdisciplinary Applications
Metin Toz, Serdar Kucuk
COMPUTER APPLICATIONS IN ENGINEERING EDUCATION
(2010)
Article
Automation & Control Systems
Metin Toz, Serdar Kucuk
ROBOTICS AND AUTONOMOUS SYSTEMS
(2013)
Article
Computer Science, Software Engineering
Metin Toz, Guliz Toz
Summary: This study explores the impact of threat factors on nature-inspired optimization algorithms and proposes a method to improve search capabilities. By simulating the relationship between wolf packs and mountain lions, it is shown that the proposed method outperforms other algorithms in terms of performance. Experimental results demonstrate that the threat factor approach does not significantly increase processing time.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Review
Computer Science, Interdisciplinary Applications
Sibel B. Ozkan, Metin Toz
Summary: This study explicitly discusses the application of robots in education, particularly in the development of metacognitive abilities. However, robots have not been fully utilized to enhance students' metacognitive skills.
COMPUTER APPLICATIONS IN ENGINEERING EDUCATION
(2022)
Article
Computer Science, Artificial Intelligence
Metin Toz, Gueliz Toz
Summary: This paper proposes an optimization algorithm based on modeling snowflake movements, considering the forces and collisions in snowfall. The algorithm outperforms PSO, WOA, BBO, GWO, BAT, and MFO in terms of exploration and exploitation abilities, except for execution time. Pairwise comparisons show that it is more stable in solving CEC 2017 and CEC 2020 benchmark problems.
EVOLUTIONARY INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Metin Toz
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
(2019)
Proceedings Paper
Automation & Control Systems
Canberk Tolunbuke, Metin Toz
2018 6TH INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING & INFORMATION TECHNOLOGY (CEIT)
(2018)
Article
Computer Science, Artificial Intelligence
Jin Zhang, Zekang Bian, Shitong Wang
Summary: This study proposes a novel style linear k-nearest neighbor method to extract stylistic features using matrix expressions and improve the generalizability of the predictor through style membership vectors.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Qifeng Wan, Xuanhua Xu, Jing Han
Summary: In this study, we propose an innovative approach for dimensionality reduction in large-scale group decision-making scenarios that targets linguistic preferences. The method combines TF-IDF feature similarity and information loss entropy to address challenges in decision-making with a large number of decision makers.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Hegui Zhu, Yuchen Ren, Chong Liu, Xiaoyan Sui, Libo Zhang
Summary: This paper proposes an adversarial attack method based on frequency information, which optimizes the imperceptibility and transferability of adversarial examples in white-box and black-box scenarios respectively. Experimental results validate the superiority of the proposed method and its application in real-world online model evaluation reveals their vulnerability.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Jing Tang, Xinwang Liu, Weizhong Wang
Summary: This paper proposes a hybrid generalized TODIM approach in the Fine-Kinney framework to evaluate occupational health and safety hazards. The approach integrates CRP, dynamic SIN, and PLTSs to handle opinion interactions and incomplete opinions among decision makers. The efficiency and rationality of the proposed approach are demonstrated through a numerical example, comparison, and sensitivity studies.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Shigen Shen, Chenpeng Cai, Zhenwei Li, Yizhou Shen, Guowen Wu, Shui Yu
Summary: To address the damage caused by zero-day attacks on SIoT systems, researchers propose a heuristic learning intrusion detection system named DQN-HIDS. By integrating Deep Q-Networks (DQN) into the system, DQN-HIDS gradually improves its ability to identify malicious traffic and reduces resource workloads. Experiments demonstrate the superior performance of DQN-HIDS in terms of workload, delayed sample queue, rewards, and classifier accuracy.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu
Summary: In this paper, we propose a Chinese text classification algorithm based on deep active learning for the power system, which addresses the challenge of specialized text classification. By applying a hierarchical confidence strategy, our model achieves higher classification accuracy with fewer labeled training data.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Kaan Deveci, Onder Guler
Summary: This study proves the lack of robustness in nonlinear IF distance functions for ranking intuitionistic fuzzy sets (IFS) and proposes an alternative ranking method based on hypervolume metric. Additionally, the suggested method is extended as a new multi-criteria decision making method called HEART, which is applied to evaluate Turkey's energy alternatives.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Fu-Wing Yu, Wai-Tung Ho, Chak-Fung Jeff Wong
Summary: This research aims to enhance the energy management in commercial building air-conditioning systems, specifically focusing on chillers. Ridge regression is found to outperform lasso and elastic net regression when optimized with the appropriate hyperparameter, making it the most suitable method for modeling the system coefficient of performance (SCOP). The key variables that strongly influence SCOP include part load ratios, the operating numbers of chillers and pumps, and the temperatures of chilled water and condenser water. Additionally, July is identified as the month with the highest potential for performance improvement. This study introduces a novel approach that balances feature selection, model accuracy, and optimal tuning of hyperparameters, highlighting the significance of a generic and simplified chiller system model in evaluating energy management opportunities for sustainable operation. The findings from this research can guide future efforts towards more energy-efficient and sustainable operations in commercial buildings.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Xiaoyan Chen, Yilin Sun, Qiuju Zhang, Xuesong Dai, Shen Tian, Yongxin Guo
Summary: In this study, a method for dynamically non-destructive grasping of thin-skinned fruits is proposed. It utilizes a multi-modal depth fusion convolutional neural network for image processing and segmentation, and combines the evaluation mechanism of optimal grasping stability and the forward-looking non-destructive grasp control algorithm. The proposed method greatly improves the comprehensive performance of grasping delicate fruits using flexible hands.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Yuxuan Yang, Siyuan Zhou, He Weng, Dongjing Wang, Xin Zhang, Dongjin Yu, Shuiguang Deng
Summary: The study proposes a novel model, POIGDE, which addresses the challenges of data sparsity and elusive motives by solving graph differential equations to capture continuous variation of users' interests. The model learns interest transference dynamics using a time-serial graph and an interval-aware attention mechanism, and applies Siamese learning to directly learn from label representations for predicting future POI visits. The model outperforms state-of-the-art models on real-world datasets, showing potential in the POI recommendation domain.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
S. Karthika, P. Rathika
Summary: The widespread development of monitoring devices in the power system has generated a large amount of power consumption data. Storing and transmitting this data has become a significant challenge. This paper proposes an adaptive data compression algorithm based on the discrete wavelet transform (DWT) for power system applications. It utilizes multi-objective particle swarm optimization (MO-PSO) to select the optimal threshold. The algorithm has been tested and outperforms other existing algorithms.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Jiaqi Guo, Haiyan Wu, Xiaolei Chen, Weiguo Lin
Summary: In this study, an adaptive SV-Borderline SMOTE-SVM algorithm is proposed to address the challenge of imbalanced data classification. The algorithm maps the data into kernel space using SVM and identifies support vectors, then generates new samples based on the neighbors of these support vectors. Extensive experiments show that this method is more effective than other approaches in imbalanced data classification.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Qiumei Zheng, Linkang Xu, Fenghua Wang, Yongqi Xu, Chao Lin, Guoqiang Zhang
Summary: This paper proposes a new semantic segmentation network model called HilbertSCNet, which combines the Hilbert curve traversal and the dual pathway idea to design a new spatial computation module to address the problem of loss of information for small targets in high-resolution images. The experiments show that the proposed network performs well in the segmentation of small targets in high-resolution maps such as drone aerial photography.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Mojtaba Ashour, Amir Mahdiyar
Summary: Analytic Hierarchy Process (AHP) is a widely applied technique in multi-criteria decision-making problems, but the sheer number of AHP methods presents challenges for scholars and practitioners in selecting the most suitable method. This paper reviews articles published between 2010 and 2023 proposing hybrid, improved, or modified AHP methods, classifies them based on their contributions, and provides a comprehensive summary table and roadmap to guide the method selection process.
APPLIED SOFT COMPUTING
(2024)
Review
Computer Science, Artificial Intelligence
Gerardo Humberto Valencia-Rivera, Maria Torcoroma Benavides-Robles, Alonso Vela Morales, Ivan Amaya, Jorge M. Cruz-Duarte, Jose Carlos Ortiz-Bayliss, Juan Gabriel Avina-Cervantes
Summary: Electric power system applications are complex optimization problems. Most literature reviews focus on studying electrical paradigms using different optimization techniques, but there is a lack of review on Metaheuristics (MHs) in these applications. Our work provides an overview of the paradigms underlying such applications and analyzes the most commonly used MHs and their search operators. We also discover a strong synergy between the Renewable Energies paradigm and other paradigms, and a significant interest in Load-Forecasting optimization problems. Based on our findings, we provide helpful recommendations for current challenges and potential research paths to support further development in this field.
APPLIED SOFT COMPUTING
(2024)