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2023 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2023

作者： Bouzid, Rania Narayan, Jyotindra Gritli, Hassene Higher Institute of Information and Communication Technologies Tunis1164 Tunisia Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Guwahati781039 India National Engineering School of Tunis Tunis1002 Tunisia

ISBN: (纸本)9798350307771

Determining an end-effector position and orientation, known as forward kinematics (FK), is a crucial aspect of robotic manipulation. This research addresses the FK problem using a Feedforward Backpropagation Artificial Neural Network (FFBP-ANN) and examines the network's performance with different hyperparameters. The input of the FFBP-ANN is primarily formed using three different datasets: fixed-step values, random values, and sinusoidal-signal based values, for a 2-DOF robotic manipulator. The output of the FFBP-ANN is evaluated using FK formulation of the robot manipulator. Thereafter, the FFBP-ANN is trained utilizing the input-output training dataset using The Neural Network Toolbox for MATLAB. The network's potential is investigated by varying the critical hyperparameters, including the number of hidden neurons and the number of hidden layers. Moreover, the effectiveness of the proposed FFBP-ANN is investigated with three different training optimizers including the utilization of Levenberg-Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient optimization algorithms. During training, by adjusting the network's weights and biases iteratively, the backpropagation technique allows the network to effectively learn and comprehend the relationship between joint positions and Cartesian coordinates. The comparative results offer valuable insights into the strengths and limitations of different ANN architectures when applied to solving FK problems. In this way, this study focuses on exploring the application of the FFBP-ANN in resolving FK challenges and assisting in the identification of appropriate network types for path-planning tasks. © 2023 IEEE.

关键词： End effectors

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Target Tracking Control of Space-Manipulators on Lie Groups

Target Tracking Control of Space-Manipulators on Lie Groups

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IEEE International Conference on Systems, Man and Cybernetics

作者： Borna Monazzah Moghaddam Robin Chhabra Mechanical and Aerospace Engineering Department Autonomous Space Robotics and Mechatronics Laboratory Carleton University Ottawa ON Canada

We present a full-pose end-effector control approach on Lie groups for free-floating space manipulators with non-zero momentum while tracking a moving target during proximity operations. We model space-manipulators as open-chain multi-body systems with 1-degree-of-freedom joints where the configuration space of the spacecraft is isomorphic to the Special Euclidean group SE(3). We formulate the dynamics of the spacecraft-manipulator via the Lagrange-Poincare equations and the dynamics of its target via Euler-Poincare equations to avoid kinematic singularities associated with parametrization of their poses. This model reduces the phase space of the space-manipulator by exploiting its inherent independence of the spacecraft's pose. We consider the full pose of the end-effector relative to the target as the system output, which transforms the output-tracking control problem into an output-regulation problem. To avoid parametrization singularities of this output, we perform feedback linearization on the matrix Lie group SE (3) in the reduced phase space of the space-manipulator. We then propose a feedback/feedforward proportional-integral-derivative workspace controller, based on coordinate-free pose and velocity error functions defined on the matrix Lie group associated with the target's relative pose. We provide analytical proof of the almost-global stability of the presented controller when regulating the end-effector's pose relative to the target towards identity.

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Exploring Neural Networks for Forward Kinematics of the Robotic Arm with Different Length Configurations: A Comparative Analysis 2

Exploring Neural Networks for Forward Kinematics of the Robo...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Bouzid, Rania Narayan, Jyotindra Gritli, Hassène Higher Institute of Information and Communication Technologies Tunis Borj Cedria1164 Tunisia Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Assam Guwahati781039 India National Engineering School of Tunis Le Belvédère Tunis1002 Tunisia

ISBN: (纸本)9798350360523

Our work investigates the utilization of Artificial Neural Networks (ANNs) to address the complexities associated with Forward Kinematics (FK) problems within the field of robotics. We undertake an extensive comparative analysis to assess how ANNs perform under different circumstances with robotic arms of varying lengths and impact the overall system's functionality. The training, testing, and validation of ANNs are carried out using MATLAB for a simulated 2-DoF serial robotic arm involving three distinct datasets: fixed step size, random step size, and sinusoidal step size. Three training optimizers, namely Levenberg Marquardt (LM), Bayesian Regularization (BR), and Stochastic Conjugate Gradient (SCG), are considered within the ANN architecture. Based on Mean Square Error (MSE) values, the numerical findings reveal the potential of ANN in estimating forward kinematic solutions of complex robotic manipulators with different arm lengths and reducing computational complexity. © 2024 IEEE.

关键词： Robotic arms

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Model heat source using actual distribution of laser power density for simulation of laser processing

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Journal of Central South University 2022年第10期29卷 3277-3293页

作者： WANG Gen-wang DING Ye GUAN Yan-chao WANG Yang YANG Li-jun State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China

The model of heat source(MHS) which reflects the thermal interaction between materials and laser during processing determines the accuracy of simulation results. To acquire desirable simulations results, although various modifications of heat sources in the aspect of absorption process of laser by materials have been purposed, the distribution of laser power density(DLPD) in MHS is still modeled theoretically. However, in the actual situations of laser processing, the DLPD is definitely different from the ideal models. So, it is indispensable to build MHS using actual DLPD to improve the accuracy of simulation results. Besides, an automatic modeling method will be benefit to simplify the tedious pre-processing of simulations. This paper presents a modeling method and corresponding algorithm to model heat source using measured DLPD. This algorithm automatically processes original data to get modeling parameters and provides a step MHS combining with absorption models. Simulations and experiments of heat transfer in steel plates irradiated by laser prove the mothed and the step MHS. Moreover, the investigations of laser induced thermal-crack propagation in glass highlight the signification of modeling heat source based on actual DLPD and demonstrate the enormous application of this method in the simulation of laser processing.

关键词： heat source laser processing distribution of power density digital images processing heat transfer

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Emotion Recognition Through EEG Signals With Movie Clips Stimuli

Emotion Recognition Through EEG Signals With Movie Clips Sti...

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Electrics and Computer (INTCEC), Interdisciplinary Conference on

作者： Jonathan Axel Cruz Vazquez Jesús Yaljá Montiel Pérez Rodolfo Romero Herrera Robotics and mechatronics laboratory IPN – CIC CDMX México Department of Computer Science and Engineering IPN – ESCOM CDMX México

ISBN: (数字)9798350349450

ISBN: (纸本)9798350349467

This study proposes a multimodal emotion recognition method acquiring electroencephalogram (EEG) data and using movie clips to express emotional stimuli. The study included 12 participants who aimed to identify three emotions: happy, sad, and neutral. For the experiments, the Emotiv Epoc+ device was used for data collection, including data preprocessing, time and frequency domain feature extraction, and classification. Emotion recognition uses different machine learning algorithms, including support vector machines (SVM), k-nearest neighbors (k-NN), random forests, and neural networks. The algorithm is trained and evaluated using feature vectors extracted from participants' emotional responses to movie videos. This method achieves a competitive accuracy of 79.09% using an SVM(POL) classifier and features including time and frequency domains.

关键词： Support vector machines Emotion recognition Visualization Accuracy Machine learning algorithms Frequency-domain analysis Feature extraction

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Comparative Study of Anti-Swing Controllers for a Triple Link Rotary Pendulum System

Comparative Study of Anti-Swing Controllers for a Triple Lin...

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IEEE International Conference on Engineering Technologies and Applied Sciences (ICETAS)

作者： Zied Ben Hazem Zafer Bingül Department of Mechatronics Engineering College of Engineering (COE) University of Technology Bahrain Bahrain Department of Mechatronics Engineering Automation and Robotics Laboratory Kocaeli University Kocaeli Turkey

This paper presents a study of the development of anti-swing control of a triple link rotary pendulum system (TLRPS). The motion nonlinear equations of the TLRPS are obtained using the Euler-Lagrange method based on the kinematic model and Denavit-Bartenberg (DH) convention. In this study three anti-swing controllers, linear-quadratic regulator (LQR), fuzzy linear-quadratic regulator (FLQR), and radial basis neuro-fuzzy linear quadratic regulator (RBNFLQR) are developed to control and eliminate the swing angles of the three links during the rotation. Moreover, the performance characteristics of the controllers are compared and examined in terms of their time response specifications parameters and swing angle elimination. Moreover, the robustness of controllers is tested under external torque disturbance. The simulation and experiment results of the response of the TLRPS are presented in time domains. Simulation and experiment results exhibit excellent control performance and robustness in terms of position control and damping oscillations elimination.

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FAST-LIVO2 on Resource-Constrained Platforms: LiDAR-Inertial-Visual Odometry With Efficient Memory and Computation

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IEEE robotics and Automation Letters 2025年第8期10卷 7931-7938页

作者： Bingyang Zhou Chunran Zheng Ziming Wang Fangcheng Zhu Yixi Cai Fu Zhang Mechatronics and Robotic Systems (MaRS) Laboratory Department of Mechanical Engineering University of Hong Kong Hong Kong SAR China Division of Robotics Perception and Learning KTH Royal Institute of Technology Stockholm Sweden

This paper presents a lightweight LiDAR-inertial-visual odometry system optimized for resource-constrained platforms. It integrates a degeneration-aware adaptive visual frame selector into error-state iterated Kalman filter (ESIKF) with sequential updates, improving computation efficiency markedly while maintaining a similar level of robustness. Additionally, a memory-efficient mapping structure combining a locally unified visual-LiDAR map and a long-term visual map achieves a good trade-off between performance and memory usage. Extensive experiments on x86 and ARM platforms demonstrate the system's robustness and efficiency. On the Hilti dataset, our system achieves a 33% reduction in per-frame runtime and 47% lower memory usage compared to FAST-LIVO2, with only a 3 cm increase in RMSE. Despite this slight accuracy trade-off, our system remains competitive, outperforming state-of-the-art (SOTA) LIO methods such as FAST-LIO2 and most existing LIVO systems. These results validate the system's capability for scalable deployment on resource-constrained edge computing platforms.

关键词： Laser radar Visualization Odometry Computational efficiency Robustness State estimation Cameras Accuracy Sensors Program processors

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Design and Control for WLR-3P:A Hydraulic Wheel-Legged Robot

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Cyborg and Bionic Systems 2023年第1期4卷 243-259页

作者： Xu Li Haoyang Yu Haibo Feng Songyuan Zhang Yili Fu State Key Laboratory of Robotics and System College of Mechatronics EngineeringHarbin Institute of TechnologyHarbin 150001China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Intelligent Robot Research Center Zhejiang LaboratoryHangzhou 311100China

The robot used for disaster rescue or field exploration requires the ability of fast moving on flat road and adaptability on complex *** hybrid wheel-legged robot(WLR-3P,prototype of the third-generation hydraulic wheel-legged robot)has the characteristics of fast and efficient mobility on flat surfaces and high environmental adaptability on rough *** this paper,3 design requirements are proposed to improve the mobility and environmental adaptability of the *** meet these 3 requirements,2 design principles for each requirement are put ***,for light weight and low inertia with high stiffness,3-dimensional printing technology and lightweight material are ***,the integrated hydraulically driven unit is used for high power density and fast response ***,the microhydraulic power unit achieves power autonomy,adopting the hoseless design to strengthen the reliability of the hydraulic *** is more,the control system including hierarchical distributed electrical system and control strategy is *** mobility and adaptability of WLR-3P are demonstrated with a series of ***,the robot can achieve a speed of 13.6 km/h and a jumping height of 0.2 m.

关键词： robot Robot terrain

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Learning-based Adaptive Admittance Controller for Efficient and Safe pHRI in Contact-rich Manufacturing Tasks

Learning-based Adaptive Admittance Controller for Efficient ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Pouya P. Niaz Engin Erzin Cagatay Basdogan Robotics and Mechatronics Laboratory (RML) and the KUIS AI Center Koc University Istanbul Turkey Multimedia Vision and Graphics Laboratory and the KUIS AI Center Koc University Istanbul Turkey

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper proposes an adaptive admittance controller for improving efficiency and safety in physical human-robot interaction (pHRI) tasks in small-batch manufacturing that involve contact with stiff environments, such as drilling, polishing, cutting, etc. We aim to minimize human effort and task completion time while maximizing precision and stability during the contact of the machine tool attached to the robot’s end-effector with the workpiece. To this end, a two-layered learning-based human intention recognition mechanism is proposed, utilizing only the kinematic and kinetic data from the robot and two force sensors. A "subtask detector" recognizes the human intent by estimating which phase of the task is being performed, e.g., Idle, Tool-Attachment, Driving, and Contact. Simultaneously, a "motion estimator" continuously quantifies intent more precisely during the Driving to predict when Contact will begin. The controller is adapted online according to the subtask while allowing early adaptation before the Contact to maximize precision and safety and prevent potential instabilities. Three sets of pHRI experiments were performed with multiple subjects under various conditions. Spring compression experiments were performed in virtual environments to train the data-driven models and validate the proposed adaptive system, and drilling experiments were performed in the physical world to test the proposed methods’ efficacy in real-life scenarios. Experimental results show subtask classification accuracy of 84% and motion estimation R 2 score of 0.96. Furthermore, 57% lower human effort was achieved during Driving as well as 53% lower oscillation amplitude at Contact as a result of the proposed system.

关键词： Drilling Adaptive systems Virtual environments Robot sensing systems Stability analysis Manufacturing Safety Admittance Springs Oscillators

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Quantifying Joint Movement Variability in Healthy and Hemiplegic Gait using OpenSim 2

Quantifying Joint Movement Variability in Healthy and Hemipl...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Rafiq, Tabassum Younis, Sadia Narayan, Jyotindra Institute of Information Management and Technology Department of Biotechnology Uttar Pradesh Aligarh202001 India Government College of Engineering and Technology Department of Biomedical Engineering Jammu and Kashmir Ganderbal193504 India Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Assam Guwahati781039 India

ISBN: (纸本)9798350360523

This study delves into the scaling capabilities of OpenSim, a biomechanical modeling tool, to scrutinize musculoskeletal alterations accompanying the hemiplegic condition compared to a healthy model. Contralateral hemiplegia (CH), characterized by unilateral paralysis, induces profound changes in bone size and significantly influences an individual's gait. Motivated by understanding the biomechanical repercussions of CH on human movement, we conducted a comprehensive investigation involving ten patients with CH, with a median age of 46 years (range: 39 to 52.0 years and height: 1.75 0.6 m). Ten healthy controls with similar body attributes were±also recruited. We assessed musculoskeletal changes post-CH using bone length data from MRI reports obtained from a hospital. Inverse kinematics in OpenSim are facilitated for a detailed comparison of joint angles between unhealthy and healthy individuals. The gait data is visualized and analyzed using statistical metrics such as mean absolute deviation, box plots, and a two-sample t-test. The results revealed significant differences in hip and ankle joint angles between healthy and hemiplegic individuals, underscored by low p-values. Interestingly, no significant difference was observed in knee joint angles (p-value = 0.9126). These findings contribute to a valuable understanding of hemiplegia-related musculoskeletal changes, offering potential avenues for tailored interventions to improve mobility and quality of life. © 2024 IEEE.

关键词： Inverse kinematics

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