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
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)
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
Thermodynamics
Hegazy Rezk, Abrar Inayat, Mohammad A. Abdelkareem, Abdul G. Olabi, Ahmed M. Nassef
Summary: This study optimized methane production from the steam gasification of palm kernel shell using fuzzy logic technique and Marine Predator Algorithm. A model was established to simulate methane production, with the optimal operating parameters identified using the MPA. Results showed a methane yield of 52.82%, surpassing traditional ANOVA methods.
Article
Automation & Control Systems
Ping-Huan Kuo, Kuan-Lin Chen
Summary: In this paper, a self-guided learning method for humanoid robots is proposed, based on deep reinforcement learning, optimization algorithms, and fuzzy logic. The method relies on proximal policy optimization to determine the optimal actions and divides the task into two steps for training the optimal models. The feasibility and effectiveness of the proposed method are validated through experiments.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Environmental Sciences
P. Mousi, V Bhuvaneswari
Summary: Water plays a vital role in all living organisms, but it is being exploited at an unsustainable rate due to rapid urbanization. This study developed an optimization approach to identify optimal sub-catchments with maximum runoff in order to implement Artificial Ground Recharge Points (AGRP) and raise the groundwater table. The research focuses on implementing AGRP in the Noyyal River basin sub-catchments in Coimbatore city, India.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
(2023)
Article
Automation & Control Systems
Haohui Huang, Chenguang Yang, C. L. Philip Chen
Summary: This article introduces a novel control strategy based on a broad fuzzy neural network (BFNN) to address the challenge of choosing a sufficient number of neural network units to approximate an unknown dynamic model. An adaptive impedance learning is developed to establish optimal interaction between the robot and the environment, while a barrier Lyapunov function is incorporated to handle state constraints and ensure stability of the closed-loop system. Simulation and experimental studies demonstrate the effectiveness of BFNN under optimal impedance control with different robotic systems.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Engineering, Aerospace
Asma Seddaoui, Chakravarthini M. Saaj
Summary: Future on-orbit servicing and assembly missions require space robots capable of manoeuvring safely. A path generator based on a Genetic Algorithm is designed to take advantage of dynamic coupling effects and controlled motion to safely achieve the target, minimizing objectives and satisfying constraints.
Article
Robotics
Jitendra Kumar, Ashish Dutta
Summary: This paper proposes a new method that integrates 3D terrain information, ditch geometry, and biped dynamics for motion planning of a 14-DOF biped robot on 3D terrain containing a 3D ditch. The method models path planning as wavefront propagation in a non-uniform medium represented by the Eikonal equation and constructs optimal trajectories using cubic spline-based trajectory generation. Simulation results demonstrate the effectiveness of the proposed ditch crossing method on different uneven terrains.
INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS
(2021)
Article
Robotics
Jitendra Kumar, Ashish Dutta
Summary: In this paper, a new method is proposed for finding a feasible energy-efficient path on uneven terrain. The method integrates information of terrain and robot dynamics to plan the path and uses numerical methods to solve the Eikonal equation. Additionally, optimization and neural network training are applied to generate optimal foot and hip trajectories.
Article
Computer Science, Information Systems
S. Zulaikha Beevi, Abdullah Alabdulatif
Summary: Wireless sensor network (WSN) is a growing field in networking, providing smart tasks for various industries. However, the limited energy in sensor nodes poses a challenge to the network's overall performance. To address this issue, researchers propose an energy efficient routing protocol using genetic fuzzy logic system, aiming to save energy by sending data packets via the shortest path. Additionally, the cluster protocol, which plays a crucial role in prolonging the sensor node's life, is utilized to select the cluster head based on factors such as maximum residual energy, head-to-head link lifetime, and minimum distance to the base station. The proposed approach achieves improved performance in terms of packet delivery and overall network throughput.
CMC-COMPUTERS MATERIALS & CONTINUA
(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
Engineering, Marine
Tsung-Hsuan Hsieh, Qian Meng, Bing Han, Shengzheng Wang, Xuezhen Wu
Summary: Determining the number and position of waypoints on a great circle route is important for optimizing sailing distance and reducing course changes. This study proposes a genetic algorithm-based method for optimizing waypoint positions, and a fuzzy logic-based evaluation method for determining the number of waypoints. The proposed methods effectively determine the waypoints and provide support for ocean route planning.
JOURNAL OF MARINE SCIENCE AND 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
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
Santosh Kumar Gupta, Susmita Datta, Sanjib Jaypuria, Dilip Kumar Pratihar, Partha Saha
ADVANCES IN MATERIALS AND MANUFACTURING ENGINEERING, ICAMME 2019
(2020)
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
Automation & Control Systems
Runwei Guan, Shanliang Yao, Lulu Liu, Xiaohui Zhu, Ka Lok Man, Yong Yue, Jeremy Smith, Eng Gee, Yutao Yue
Summary: With the development of Unmanned Surface Vehicles (USVs), the perception of inland waterways has become significant. Traditional RGB cameras cannot work effectively in adverse weather and at night, which has led to the emergence of 4D millimeter-wave radar as a new perception sensor. However, the radar suffers from water-surface clutter and irregular shape of point cloud. To address these issues, this paper proposes a high-performance panoptic perception model called Mask-VRDet, which fuses features of vision and radar using graph neural network.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Adrien Le Reun, Kevin Subrin, Anthony Dubois, Sebastien Garnier
Summary: This study aims to evaluate the quality and health of aerospace parts using a high-dimensional robotic cell. By utilizing X-ray Computed Tomography devices, the interior of the parts can be reconstructed and anomalies can be detected. A methodology is proposed to assess both the raw process capability and the improved process capability, with three strategies developed to improve the robot behavior model and calibration.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Weiming Ba, Jung-Che Chang, Jing Liu, Xi Wang, Xin Dong, Dragos Axinte
Summary: This paper proposes a hybrid scheme for kinematic control of continuum robots, which avoids errors through tension supervision and accurate piecewise linear approximation. The effectiveness of the controller is verified on different continuum robotic systems.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Gabriele Abbate, Alessandro Giusti, Viktor Schmuck, Oya Celiktutan, Antonio Paolillo
Summary: In this study, a learning-based approach is proposed to predict the probability of human users interacting with a robot before the interaction begins. By considering the pose and motion of the user, the approach labels the robot's encounters with humans in a self-supervised manner. The method is validated and deployed in various scenarios, achieving high accuracy in predicting user intentions to interact with the robot.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Tiago Cortinhal, Eren Erdal Aksoy
Summary: This work presents a new depth-and semantics-aware conditional generative model, named TITAN-Next, for cross-domain image-to-image translation between LiDAR and camera sensors. The model is able to translate raw LiDAR point clouds to RGB-D camera images by solely relying on semantic scene segments, and it has practical applications in fields like autonomous vehicles.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Marios Krestenitis, Emmanuel K. Raptis, Athanasios Ch. Kapoutsis, Konstantinos Ioannidis, Elias B. Kosmatopoulos, Stefanos Vrochidis
Summary: This paper addresses the issue of informative path planning for a UAV used in precision agriculture. By using a non-uniform scanning approach, the time spent in areas with minimal value is reduced, while maintaining high precision in information-dense regions. A novel active sensing and deep learning-based coverage path planning approach is proposed, which adjusts the UAV's speed based on the quantity and confidence level of identified plant classes.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shota Kokubu, Pablo E. Tortos Vinocour, Wenwei Yu
Summary: In this study, a new modular soft actuator was proposed to improve the support performance of soft rehabilitation gloves (SRGs). Objective evaluations and clinical tests were conducted to demonstrate the effectiveness and functionality of the proposed actuator and SRG.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Jinliang Zhu, Yuanxi Sun, Jie Xiong, Yiyang Liu, Jia Zheng, Long Bai
Summary: This paper proposes an active prosthetic knee joint with a variable stiffness parallel elastic actuation mechanism. Numerical verifications and practical experiments demonstrate that the mechanism can reduce torque and power, thus reducing energy consumption and improving the endurance of the prosthetic knee joint.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Yong You, Jingtao Wu, Yunlong Meng, Dongye Sun, Datong Qin
Summary: A new power-cycling variable transmission (PCVT) is proposed and applied to construction vehicles to improve transmission efficiency. A shift correction strategy is developed based on identifying the changes in construction vehicles' mass and gradient. Simulation results show that the proposed method can correct shift points, improve operation efficiency, and ensure a safer operation process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shaorui Liu, Wei Tian, Jianxin Shen, Bo Li, Pengcheng Li
Summary: This paper proposes a two-objective optimization technique for multi-robot systems, addressing the issue of balancing productivity and machining performance in high-quality machining tasks.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pengchao Ding, Faben Zhu, Hongbiao Zhu, Gongcheng Wang, Hua Bai, Han Wang, Dongmei Wu, Zhijiang Du, Weidong Wang
Summary: We propose an autonomous approaching scheme for mobile robot traversing obstacle stairwells, which overcomes the restricted field of vision caused by obstacles. The scheme includes stair localization, structural parameter estimation, and optimization of the approaching process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pedro Azevedo, Vitor Santos
Summary: Accurate detection and tracking of vulnerable road users and traffic objects are vital tasks for autonomous driving and driving assistance systems. This paper proposes a solution for object detection and tracking in an autonomous driving scenario, comparing different object detectors and exploring the deployment on edge devices. The effectiveness of DeepStream technology and different object trackers is assessed using the KITTI tracking dataset.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Benjamin Beiter, Divya Srinivasan, Alexander Leonessa
Summary: Powered exoskeletons can significantly reduce physical workload and have great potential impact on future labor practices. To truly assist users in achieving task goals, a shared autonomy control framework is proposed to separate the control objectives of the human and exoskeleton. Positive Power control is introduced for the human-based controller, while 'acceptance' is used as a measure of matching the exoskeleton's control objective to the human's. Both control objectives are implemented in an optimization-based Whole-Body-Control structure. The results verify the effectiveness of the control framework and its potential for improving cooperative control for powered exoskeletons.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)