Article
Computer Science, Information Systems
Daegyun Choi, Donghoon Kim
Summary: This study proposes an intelligent and decentralized approach for a multi-robot system using a genetic fuzzy system to perform an object transportation mission and ensure the stability of the overall system in a rough terrain environment.
Article
Engineering, Chemical
Chia-Wen Chang, Chin-Wang Tao
Summary: This paper presents a fuzzy motion control algorithm for a monocular vision system in a cooperative transportation system of two humanoid robots. The algorithm includes three stages: object searching, walking towards the transported object, and cooperating to move the object. The algorithm utilizes fuzzy techniques for synchronous movement control.
Article
Automation & Control Systems
Lingxuan Zhao, Zhangguo Yu, Lianqiang Han, Xuechao Chen, Xuejian Qiu, Qiang Huang
Summary: Wheeled-legged humanoid robots combine humanoid robot's terrain adaptability and wheeled robot's efficiency. However, stability control in dealing with rough terrains and external disturbances remains unsolved. This research proposes a compliant balance control framework that can absorb shocks, withstand disturbances, and maintain stable motion.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Engineering, Mechanical
Zebang Pan, Shan Yin, Guilin Wen, Zhao Tan
Summary: Designing a high-performance controller for biped robots' walking gaits is a research area that is still open due to their nonlinearity and non-smooth responses. To overcome these challenges, a humanoid robot with a torso is developed first, followed by the adoption of the twin delayed deep deterministic policy gradient algorithm to design the reinforcement learning controller. A reward function utilizing the Poincare map and the power function is constructed for the specified control targets, providing guidelines for the controller. The proposed controller can adaptively output accurate cosine torques and achieve the goal without relying on pre-designed reference trajectories or unstable periodic gaits.
ACTA MECHANICA SINICA
(2023)
Review
Robotics
Moh Shahid Khan, Ravi Kumar Mandava
Summary: This review article discusses the challenges in biped gait generation and controller design on various terrains, and provides a comprehensive compilation of research work in this area. The authors found that no single study has examined the gait generation and controller design for each joint of biped robots on different terrains. The review aims to help researchers better understand the concepts of gait generation and controller design while moving on various terrains.
Article
Robotics
Mathieu Hobon, Victor De-Leon-Gomez, Gabriel Abba, Yannick Aoustin, Christine Chevallereau
Summary: The study aims to define the feasible speed range for two walking motions of a particular planar biped robot, revealing that the first gait is more energy-efficient at moderate to fast velocities, while the second gait is more efficient at low walking speeds. The results were obtained through numerical calculations and a parametric optimization algorithm.
Article
Computer Science, Information Systems
Chul-Hong Kim, Dong-Il Cho
Summary: This paper proposes a DNN-based slip ratio estimator fused with IEKF for lugged-wheel robot localization. The proposed localization method is robust to wheel slippage in outdoor environments. Experimental results show significant reduction in localization errors compared to integration-based localization and IEKF-based localization.
Article
Computer Science, Artificial Intelligence
Abhishek Jhawar, Chee Kau Lim, Chee Seng Chan
Summary: This paper aims to study fall prevention and develop a ranking system to aid in reducing fall incidents. The proposed approach is validated by experimental data and is proven to be effective and reliable.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Multidisciplinary
Zihan Xu, Qin Fang, Yong Ren, Chengju Liu
Summary: In this paper, an active balance control framework is proposed for position-controlled robots, which includes a compliant controller and a fuzzy footstep planner. The framework addresses the challenges of force estimation and footstep generation. Experimental results validate the effectiveness and robustness of the proposed framework.
JOURNAL OF BIONIC ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Guanfeng Zhou, Bo Jiang, Tengfei Long, Guirong Jiang
Summary: This article presents a biped robot walking on horizontal ground with two feasible switching patterns of motion (two-phase gait and three-phase gait). By using the first-order Taylor approximate at the equilibrium point, a simplified linear continuous dynamic equation is obtained to discuss the walking dynamics of the biped robot. Conditions for the existence and stability of period-1 gaits (P(1,2),P(1,3)) and period-2 gaits (P(2,2,2),P(2,2,3),P(2,3,3)) are obtained by using a discrete map. Among the periodic gaits, the P(2,2,3) type gait has never been reported in previous studies. Flip bifurcation of periodic gait is investigated. Numerical results for periodic gaits and bifurcation diagram are in good agreement with the theoretical analysis.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2023)
Article
Multidisciplinary Sciences
Pengyu Zhao, Anhuan Xie, Shiqiang Zhu, Lingyu Kong
Summary: This paper proposes an electric-hydraulic hybrid drive system for biped robots to address the issues of low output torque, weak impact resistance, and high energy consumption in traditional drive systems. The robot platform is designed based on the Zhejiang Lab biped robot prototype, and models of the hydraulic drive system and mechanical structure are established to analyze dynamic characteristics and load forces during walking. A value function reflecting the energy consumption of the hydraulic drive system is proposed, with the pressure of the accumulator in the hydraulic power unit selected as the control parameter. The control parameters are optimized using a genetic algorithm to minimize the value function, thereby reducing energy consumption of the hydraulic drive system. Simulation results show that the proposed optimization algorithm improves efficiency by 3.49%.
SCIENTIFIC REPORTS
(2023)
Article
Mathematics
Jiarui Chen, Aimin Tang, Guanfeng Zhou, Ling Lin, Guirong Jiang
Summary: This study presents an ascending stair biped robot model with impulse thrust and obtains the conditions for the existence and stability of period-1 gait through linearization and discrete mapping. Numerical simulations validate the feasibility of theoretical analysis.
ELECTRONIC RESEARCH ARCHIVE
(2022)
Article
Computer Science, Information Systems
Kunming Zheng, Qiuju Zhang, Youmin Hu, Bo Wu
Summary: This study addresses the control problem of complex robot systems with uncertainties and disturbances using the FS-FNN-BSC system, which guarantees accurate, stable and efficient control. By utilizing fuzzy system and fuzzy neural network technologies, modeling and non-modeling information is approximated and predicted, respectively. The stability of the FS-FNN-BSC system is proved based on the Lyapunov stability theorem, and its superiority is demonstrated through quantitative comparison with existing intelligent control methods on the series and parallel robots.
INFORMATION SCIENCES
(2021)
Article
Automation & Control Systems
E. Xidias, V Moulianitis, P. Azariadis
Summary: This paper focuses on determining the near optimum route of a manipulator's end-effector to reach a predefined set of demand points in a robotic work cell. A new approach is presented for planning collision-free motion and scheduling time near optimum route along the demand points, utilizing a combination of a geometrical approach and an adaptive neuro-fuzzy system to consider multiple manipulator configurations, and a special genetic algorithm to solve the optimization problem. The experiments demonstrate that the proposed method can determine both the near optimum manipulator configurations and the near optimum sequence of demand points.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
D. P. Acharjya, R. Rathi
Summary: This paper introduces a model that combines fuzzy rough set, real-coded genetic algorithm, and linear regression for predicting decision values of unseen instances in smart agriculture. The model goes through two phases - using fuzzy rough set to eliminate unnecessary attributes in the first phase, and employing real-coded genetic algorithm with linear regression in the second phase. The viability of the proposed model is assessed using agricultural information system data from a specific district in India, and its accuracy is compared with existing techniques.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Engineering, Mechanical
Debasish Das, Amit Kr Das, D. K. Pratihar, G. G. Roy
Summary: Machine learning algorithms were used to predict residual stress during electron beam welding of stainless steel, with support vector regression and locally weighted learning showing consistent good and bad performance respectively. Experimental validation through X-ray diffraction showed good agreements, while statistical tests and Monte-Carlo simulations were used to analyze the reliability of the employed models.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2021)
Review
Materials Science, Multidisciplinary
Debasish Das, Sanjib Jaypuria, Dilip Kumar Pratihar, Gour Gopal Roy
Summary: Optimisation has been extensively used in welding to determine optimal input parameters for desired weld attributes and accurately establish an input-output relationship of the welding process. Both traditional and nature-inspired optimisation tools have been utilized for these purposes. Future research areas in the role of optimisation in welding have also been identified.
SCIENCE AND TECHNOLOGY OF WELDING AND JOINING
(2021)
Article
Computer Science, Artificial Intelligence
Amit Kumar Das, Dilip Kumar Pratihar
Summary: A novel mutation scheme and crossover operator are proposed for improving the performance of genetic algorithm in solving real-coded problems, and experiments show that the proposed algorithm outperforms others in terms of accuracy, convergence rate, and computational time.
Article
Computer Science, Artificial Intelligence
Debasish Das, Amit Kumar Das, Abhishek Rudra Pal, Sanjib Jaypuria, Dilip Kumar Pratihar, Gour Gopal Roy
Summary: The study models electron beam welding through Elman and Jordan recurrent neural networks, trained using nature-inspired optimization tools. Experimental results show that the flower pollination-tuned Jordan RNN yields the best prediction results.
NEURAL PROCESSING LETTERS
(2021)
Article
Engineering, Mechanical
Kondalarao Bhavanibhatla, Sulthan Suresh-Fazeela, Dilip Kumar Pratihar
Summary: This study conducted numerical analysis to determine the optimal mounting location for the base of a serial manipulator on a six-legged mobile platform, taking into account factors such as workspace, manipulability, and foot forces' distribution.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Amit Kumar Das, Dilip Kumar Pratihar
Summary: This paper introduces an intelligent optimization technique called Bonobo Optimizer (BO), which mimics the reproductive strategies and social behavior of Bonobos. The BO is designed to efficiently solve optimization problems by incorporating natural strategies and a unique searching mechanism. Results from testing BO on various functions and real-life optimization problems show its applicability and superior performance compared to other algorithms.
APPLIED INTELLIGENCE
(2022)
Article
Engineering, Electrical & Electronic
Saikat Sahoo, Shivam Kumar Panda, Dilip Kumar Pratihar, Sudipta Mukhopadhyay
Summary: This article proposes a novel method for recognizing locomotion mode and estimating environmental features using laser distance sensors and inertial measurement units. The efficiency of this method was tested with healthy subjects and proved to be accurate and effective for controlling lower limb prosthetic devices.
IEEE SENSORS JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Amit Kumar Das, Saikat Sahoo, Dilip Kumar Pratihar
Summary: The necessity of developing orthotic devices for stroke or spinal injury patients has led to the need for more compact and energy efficient designs. In this study, a novel optimal design of an energy-economic knee orthosis has been obtained using the Self-adaptive Bonobo Optimizer (SaBO) algorithm. SaBO has been proven to outperform other optimization techniques in solving difficult benchmark functions and has successfully yielded the most energy-efficient design for knee orthosis, reducing the required maximum motor torque by up to 22%.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2023)
Article
Robotics
Pushpendra Gupta, Dilip Kumar Pratihar, Kalyanmoy Deb
Summary: The gait cycle of the 25-degree of freedom humanoid robot NAO consists of single support phase and double support phase. Both dynamic and stability analyses are conducted to determine its power consumption and dynamic stability margin. Particle swarm optimization and genetic algorithms are used to optimize the single support phase and double support phase separately, and the results show that particle swarm optimization performs better. The study also reveals that a humanoid robot with higher hip height, lower swing height, and slower pace consumes less power during the gait cycle.
INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS
(2023)
Article
Multidisciplinary Sciences
Sanjib Jaypuria, Amit Kumar Das, P. K. C. Kanigalpula, Debasish Das, Dilip Kumar Pratihar, Debalay Chakrabarti, M. N. Jha
Summary: The input-output relationships of electron beam welding are nonlinear and complex. ANFIS-based input-output modeling is used to predict the severity of spiking. Optimization algorithms like grey wolf optimizer, particle swarm optimization, and bonobo optimizer are used to optimize the ANFIS architecture and achieve precise predictions. Multi-objective optimization algorithms are used to solve the conflicting multi-objective criteria problems.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Saikat Sahoo, Dilip Kumar Pratihar, Sudipta Mukhopadhyay
Summary: A novel gait event detection strategy was proposed in this study, which demonstrated improved overall performance by adapting to different locomotion modes through LM classification and rule-base selection.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Multidisciplinary Sciences
Amit Kumar Das, Debasish Das, Sanjib Jaypuria, Dilip Kumar Pratihar, Gour Gopal Roy
Summary: This study utilized ANFIS models to predict weld attributes during EBW of SS201 and found the best prediction accuracy in multi-objective optimization. Interesting observations were made during the experiment, such as the fixed input power and squeezed experimental range for welding speed.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Proceedings Paper
Engineering, Manufacturing
Sanjib Jaypuria, Santosh Kumar Gupta, Dilip Kumar Pratihar
ADVANCES IN ADDITIVE MANUFACTURING AND JOINING, AIMTDR 2018
(2020)
Proceedings Paper
Engineering, Manufacturing
Biswesh Ranjan Acharya, Abhijeet Sethi, Akhil Dindigala, Partha Saha, Dilip Kumar Pratihar
ADVANCES IN UNCONVENTIONAL MACHINING AND COMPOSITES, AIMTDR 2018
(2020)
Article
Multidisciplinary Sciences
Debasish Das, Dilip Kumar Pratihar, Gour Gopal Roy
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2020)
Article
Computer Science, Interdisciplinary Applications
Shenglin Wang, Jingqiong Zhang, Peng Wang, James Law, Radu Calinescu, Lyudmila Mihaylova
Summary: In Industry 5.0, Digital Twins provide flexibility and efficiency for smart manufacturing. Deep learning techniques are used to enhance the Digital Twin framework, enabling the detection and classification of human operators and robots during the manufacturing process. The framework shows promising results in accurately detecting and classifying actions of human operators and robots in various scenarios.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yi Liu, Junpeng Qiu, Jincheng Wang, Junhe Lian, Zeran Hou, Junying Min
Summary: In this study, a double-sided robotic roller forming process was developed to form ultrahigh strength steels to thin-walled profiles. Synchronized laser heating and iterative path compensation method were used to reduce forming forces and achieve high-precision forming.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zequn Zhang, Yuchen Ji, Dunbing Tang, Jie Chen, Changchun Liu
Summary: This paper proposes a digital twin system for human-robot collaboration (HRC) that overcomes the limitations of current methods and improves the overall performance. The system includes a human mesh recovery algorithm and uncertainty estimation to enhance the system's capabilities. Experimental results demonstrate the superiority of the proposed methods over baseline methods. The feasibility and effectiveness of the HRC system are validated through a case study involving component assembly.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Junmin Park, Taehoon Kim, Chengyan Gu, Yun Kang, Joono Cheong
Summary: This paper proposes a highly reliable and accurate collision estimator for robot manipulators in human-robot collaborative environments using the Bayesian approach. By assuming robot collisions as dynamic Markov processes, the estimator can integrate prior beliefs and measurements to produce current beliefs in a recursive form. The method achieves compelling performance in collision estimation with high accuracy and no false alarms.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Meng Wang, Kaixuan Chen, Panfeng Wang, Yimin Song, Tao Sun
Summary: In this study, a novel teleoperation machining mode and control strategy were proposed to improve efficiency and accuracy in small batch production of large casting parts. By using variable motion mapping and elastic compensation, constant cutting force was achieved, and the workpiece was protected by employing forbidden virtual fixtures and movement constraints on the slave robot.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhaoyu Li, Dong He, Xiangyu Li, Xiaoke Deng, Pengcheng Hu, Jiancheng Hao, Yue Hou, Hongyu Yu, Kai Tang
Summary: This paper presents a novel algorithm for planning a five-axis inspection path for arbitrary freeform surfaces. By converting the inspection path planning problem into a set-covering problem, the algorithm generates a near-minimum set of inspection paths that satisfy necessary constraints. Both computer simulation and physical inspection experiments confirm the effectiveness and advantages of the proposed method.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang, Rui Huang
Summary: This paper introduces a novel framework based on deep reinforcement learning for generating machining process routes for designated parts. The framework utilizes graph representations of parts and employs convolutional graph neural networks for effective processing. Experimental results demonstrate the ability of the proposed method to generate efficient machining process routes and overcome limitations of traditional methods.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Regina Kyung-Jin Lee, Hao Zheng, Yuqian Lu
Summary: Future manufacturing will witness a shift towards collaboration and compassion in human-robot relationships. To enable seamless knowledge transfer, a unified knowledge representation system that can be shared by humans and robots is essential. The Human-Robot Shared Assembly Taxonomy (HR-SAT) proposed in this study allows comprehensive assembly tasks to be represented as a knowledge graph that is understandable by both humans and robots. HR-SAT incorporates rich assembly information and has diverse applications in process planning, quality checking, and human-robot collaboration.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Jianhui He, Lefeng Gu, Guilin Yang, Yiyang Feng, Silu Chen, Zaojun Fang
Summary: This paper presents a new modular kinematic error model for collaborative robots and proposes a portable self-calibration device to improve their positioning accuracy.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hongwei Sun, Jixiang Yang, Han Ding
Summary: This paper proposes an asymmetrical FIR filter-based tool path smoothing algorithm to fully utilize the joint drive capability of robot manipulators. The algorithm considers the pose-dependent dynamics and constraints of the robot and improves motion efficiency by over 10% compared to traditional methods.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Dongsheng Ge, Huan Zhao, Yiwei Wang, Dianxi Li, Xiangfei Li, Han Ding
Summary: This paper focuses on learning a stable force control policy from human demonstration during contact transients. Based on the analysis of human demonstration data, a novel human-inspired force control strategy called compliant dynamical system (CDS) is proposed. The effectiveness of the proposed method is validated through simulation and real-world experiments.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Xuepeng Huang, Zhenzhong Wang, Lucheng Li, Qi Luo
Summary: This study models the stiffness of a robot and modifies the tool influence function (TIF) with the Preston equation in order to achieve uniform surface quality in robotic bonnet polishing (RBP) of optical components. Experimental results validate the accuracy of the modified model.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Mario D. Fiore, Felix Allmendinger, Ciro Natale
Summary: This paper presents a constraint-based programming framework for task specification and motion optimization. The framework can handle constraints on robot joint and Cartesian coordinates, as well as time dependency. It also compares with existing methods and provides numerical support through illustrative examples and case studies.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yongxue Chen, Yaoan Lu, Ye Ding
Summary: This paper presents an optimization method for directly generating a six-degree-of-freedom toolpath for robotic flank milling. By optimizing the smoothness of the toolpath and the stiffness of the robot, the efficiency, accuracy, and finish of the machining are improved.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Chungang Zhuang, Haoyu Wang, Han Ding
Summary: This article proposes an end-to-end pipeline for synchronously regressing potential object poses from an unsegmented point cloud. It extracts point pair features and uses a voting architecture for instance feature extraction, along with a 3D heatmap for clustering votes and generating center seeds. An attention voting module is also employed to adaptively fuse point-wise features into instance-wise features. The network demonstrates robustness and improved performance in pose estimation.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
