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12th RSI International Conference on robotics and Mechatronics, ICRoM 2024

作者： Ardakani, Alireza Kamali Akbari, Hossein Namazian, Parsa Masouleh, Mehdi Tale Bahrami, Arash University of Tehran Human and Robot Interaction Laboratory School of Mechanical Engineering Tehran Iran University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran School of Mechanical Engineering University of Tehran Tehran Iran

ISBN: (纸本)9798331529734

This paper presents the dynamic modeling and analysis of a hyper-redundant manipulator with two Gough-Stewart platforms. Initially, the kinematic model of the manipulator is reviewed and used, since it acts as a base component for the subsequent dynamic modeling. Then, the virtual work approach is introduced to establish a foundation for the dynamic modeling of a single Gough-Stewart platform. This modeling for a single segment is used to form the equation of motion for both segments. However, the external forces applied to the lower Gough-Stewart robot are different from the upper one, since the force and masses in the upper platform act on the lower one. By considering these effects on the lower platform, the dynamic equations for the whole have been formed and presented. The accuracy of the proposed model is validated through a detailed comparison with simulations performed using a Simscape environment. Notable challenges in aligning the results between the model and simulations are discussed, highlighting the complexities involved in ensuring consistency across different platforms. The comparisons show an average error of 1.537 percent per actuator. © 2024 IEEE.

关键词： Digital elevation model

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Autonomous robotic Assembly and Sequence Planning Based on YOLOv8 11

Autonomous Robotic Assembly and Sequence Planning Based on Y...

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11th RSI International Conference on robotics and Mechatronics, ICRoM 2023

作者： Babi, Zeynab Ezzati Khomami, Navid Asadi Masouleh, Mehdi Tale Kalhor, Ahmad University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran School of Mechanical Engineering Human and Robot Interaction Laboratory Tehran Iran

ISBN: (纸本)9798350308105

This study contributes to autonomous assembly by introducing a robotic building system designed to observe its workspace, plan building sequences, determine appropriate grasps and manipulator motions, and operate hardware in real-time. This study involves the creation of a wooden brick dataset and employs a YOLOv8 deep learning model for object segmentation in two implemented real-time algorithms, namely, Desired Construction Object Detection (DCOD) and robot Current Frame Object Detection (RCFOD). The DCOD algorithm is designed for the desired structure, while the RCFOD algorithm is utilized for detecting objects within the operational environment of the robot. By comparing the outputs of these two algorithms, sequences of objects for assembly are formulated, and the appropriate grasp positions are determined. Subsequently, the robot's motion planning for both grasping and construction tasks is executed. Due to the limitations of using a single RGB gripper-mounted camera, various issues, such as failing to recognize items with the same cross-section but varying heights, have been addressed in this study. The results of this study indicate the effective learning of the YOLOv8 model, as shown by a loss value below 0.2 and an accuracy over 90% for 17 out of the total 18 classes. Practical implementation is done by a common industrial Delta parallel robot, a 2-finger gripper, and a simple RGB camera. Overview of practical implementation system is shown in Fig. 1. The proposed robotic assembly method demonstrates its effectiveness in autonomously constructing structures utilizing a reduced and cost-efficient configuration. © 2023 IEEE.

关键词： Object detection

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AGILE: Approach-based Grasp Inference Learned from Element Decomposition 11

AGILE: Approach-based Grasp Inference Learned from Element D...

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11th RSI International Conference on robotics and Mechatronics, ICRoM 2023

作者： Koosheshi, Mohammadhossein Hosseini, Hamed Masouleh, Mehdi Tale Kalhor, Ahmad Yazdi, Mohammad Reza Hairi University of Tehran Human and Robot Interaction Laboratory School of Mechanical Engineering Iran University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Iran University of Tehran School of Mechanical Engineering College of Engineering Iran

ISBN: (纸本)9798350308105

humans, this species expert in grasp detection, can grasp objects by taking into account hand-object positioning information. This work proposes a method to enable a robot manipulator to learn the same, grasping objects in the most optimal way according to how the gripper has approached the object. Built on deep learning, the proposed method consists of two main stages. In order to generalize the network on unseen objects, the proposed Approach-based Grasping Inference involves an element decomposition stage to split an object into its main parts, each with one or more annotated grasps for a particular approach of the gripper. Subsequently, a grasp detection network utilizes the decomposed elements by Mask R-CNN and the information on the approach of the gripper in order to detect the element the gripper has approached and the most optimal grasp. In order to train the networks, the study introduces a robotic grasping dataset collected in the Coppeliasim simulation environment. The dataset involves 10 different objects with annotated element decomposition masks and grasp rectangles. The proposed method acquires a 90% grasp success rate on seen objects and 78% on unseen objects in the Coppeliasim simulation environment. Lastly, simulation-to-reality domain adaptation is performed by applying transformations on the training set collected in simulation and augmenting the dataset, which results in a 70% physical grasp success performance using a Delta parallel robot and a 2 -fingered gripper. © 2023 IEEE.

关键词： Grippers

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Design and Fabrication of an Optimized Six-Axis Force-Torque Sensor 11

Design and Fabrication of an Optimized Six-Axis Force-Torque...

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11th RSI International Conference on robotics and Mechatronics, ICRoM 2023

作者： Ehsani, Amirhossein Khomami, Navid Asadi Ghaneie, Meysam Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

Force-torque sensors hold significant applications across various industries, including industrial automation, robotics, aerospace, medicine, and laboratory settings. In this paper the purpose is to optimize, simulate, and fabricate a six-axis force-torque sensor capable of measuring forces and torques along x, y and z axes. This endeavor faces challenges, including the meticulous installation of strain gauges, the design of an optimal structure and the creation of a sensor which is not excessively complex to fabricate. Careful attention is devoted to precise installation of strain gauges due to their sensitivity and crucial role in accurate measurement. Furthermore, the sensor structure is strategically designed to be optimal yet not intricate to fabricate, balancing between accuracy, optimality and feasibility of fabrication. Utilizing a genetic optimization algorithm with multi-objective functions instead of single-objective functions, this paper aims to determine the optimal dimensions. The application of multi-objective functions allows for more nuanced and flexible optimization process, catering to the complex requirements of the sensor design. Subsequently, the final design is simulated using ANSYS software to create a finite element model, providing a detailed analysis of the sensor's behavior under various conditions. This approach ensures a comprehensive understanding of the sensor's characteristics and limitations. A comprehensive analysis of the results is carried out, with the primary objective of minimizing manufacturing costs while ensuring that performance characteristics, such as an accuracy level of lOmN for force axes and 3.5mNm for torques, are demonstrated by the sensor. In order to sense strains, 16 Double strain gauges are employed. Sensor circuits are configured using six Wheatstone bridges, and calibration procedure is operated using a setup constructed in human and robot interaction laboratory. © 2023 IEEE.

关键词： human robot interaction

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Experimental Study on Chess Board Setup Using Delta Parallel robot Based on Deep Learning 11

Experimental Study on Chess Board Setup Using Delta Parallel...

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11th RSI International Conference on robotics and Mechatronics, ICRoM 2023

作者： Yarmohammadi, Parsa Khomami, Navid Asadi Masouleh, Mehdi Tale Zakerzadeh, Mohammad Reza University of Tehran Human and Robot Interaction Laboratory School of Mechanical Engineering Tehran Iran University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran University of Tehran School of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

In recent years, robotics and object detection applications have seen remarkable improvements in executing routine tasks. In the near future, it is expected that most of the tasks can be performed by means of these two foregoing tools. This paper presents a system that combines these two approaches in order to automate the setup of a chessboard using a Delta parallel robot equipped with a two-finger gripper designed for grasping small objects. This system utilizes the so-called YOLO model for object detection in order to detect the chess pieces. The system begins by taking a picture of a scene, where the chess pieces are placed randomly around a board. The location of the chessboard is predefined and YOLO is used to detect and locate chess pieces in the given picture. The final object detection model used to execute this task is YOLOv5m, although this model encountered some challenges in detecting four types of chess pieces from a top view, these challenges were addressed by increasing the instances of those objects in the dataset. Upon extracting the location of each piece, the coordinates are sent to the robot, and the Delta parallel robot arranges the initial setup of a chess game. The model achieved an overall mAP of 0.99, indicating excellent precision and the grasp success rate in the process of grasping the chess pieces was 95%. This study demonstrates the potential of automating everyday tasks by exploring the intersection of robotics and artificial intelligence and can be well extended to tasks, namely, sorting medications and pills in hospitals, sorting different wastes like plastic and papers for recycling, identifying and removing spoiled fruits in agricultural industries, etc. © 2023 IEEE.

关键词： Object detection

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Configuration and Kinematics of a 3-DOF Generalized Spherical Parallel Mechanism for Ankle Rehabilitation

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Chinese Journal of mechanical engineering 2024年第1期37卷 176-188页

作者： Jianjun Zhang Shuai Yang Chenglei Liu Xiaohui Wang Shijie Guo School of Mechanical Engineering Hebei University of TechnologyTianjin 300401China Key Laboratory of Robot Perception and Human-Machine Fusion Tianjin 300401China

The kinematic equivalent model of an existing ankle-rehabilitation robot is inconsistent with the anatomical structure of the human ankle,which influences the rehabilitation ***,this study equates the human ankle to the UR model and proposes a novel three degrees of freedom(3-DOF)generalized spherical parallel mechanism for ankle *** parallel mechanism has two spherical centers corresponding to the rotation centers of tibiotalar and subtalar *** screw theory,the mobility of the parallel mechanism,which meets the requirements of the human ankle,is *** inverse kinematics are presented,and singularities are identified based on the Jacobian *** workspaces of the parallel mechanism are obtained through the search method and compared with the motion range of the human ankle,which shows that the parallel mechanism can meet the motion demand of ankle ***,based on the motion-force transmissibility,the performance atlases are plotted in the parameter optimal design space,and the optimum parameter is obtained according to the demands of practical *** results show that the parallel mechanism can meet the motion requirements of ankle rehabilitation and has excellent kinematic performance in its rehabilitation range,which provides a theoretical basis for the prototype design and experimental verification.

关键词： Ankle rehabilitation Parallel mechanism Kinematic analysis Parameter optimization

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Workspace Calculation of the 2(6-UPS) Hybrid Manipulator 12

Workspace Calculation of the 2(6-UPS) Hybrid Manipulator

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12th RSI International Conference on robotics and Mechatronics, ICRoM 2024

作者： Gheybi, Mohammad Mahdi Moghimi, Hediye Namazian, Parsa Varshovi-Jaghargh, Payam Masouleh, Mehdi Tale School of Mechanical Engineering University of Tehran Human and Robot Interaction Laboratory Tehran Iran Hamedan University of Technology Department of Mechanical Engineering Hamedan Iran

ISBN: (纸本)9798331529734

This paper presents an algorithm for computing the workspace of the hybrid serial-parallel manipulator. In this method, the inverse kinematics problem and interval analysis are applied to determine the constant-orientation workspace of the 6-UPS parallel manipulator. Then, the workspace of the 2(6-UPS) hybrid manipulator is calculated by combining this approach with the discretization method. The results show that the development of this method provides fast and accurate results for calculating the workspace of the hybrid serial-parallel manipulator. © 2024 IEEE.

关键词： Inverse kinematics

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SPAR-Leg: Serial-Parallel Anthropomorphic robotic Leg 11

SPAR-Leg: Serial-Parallel Anthropomorphic Robotic Leg

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11th RSI International Conference on robotics and Mechatronics, ICRoM 2023

作者： Namazian, Parsa Masouleh, Mehdi Tale Zakerzadeh, Mohammad Reza University of Tehran Human and Robot Interaction Laboratory School of Mechanical Engineering Tehran Iran University of Tehran Human and Robot Interaction Laboratory School of Eletrical Computer Engineenng Tehran Iran University of Tehran School of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

This paper aims at a preliminary research on designing a hybrid mechanism inspired by human leg's musculoskeletal architecture and locomotion capabilities. Complexity of the workspace solution in serial-parallel mechanisms limits the design approach. In order to have an estimation from the human leg geometry and reachable workspace, a dataset is collected from the human leg of 10 females and 10 males. In addition to the measurements done on the dimensions of this population, the reachable workspace of their leg is observed using MediaPipe pose estimation model. This is done by capturing full movement of the human leg for each person in front of two cameras. On the other hand, the musculoskeletal system of the human leg reveals that two serially attached parallel mechanisms are well-suited for the design. The upper mechanism, which is the thigh mechanism, includes 6 UPS links as the actuators, and a US constraint link to avoid elongation in the leg. Similarly, 3 UPS and a S constraint link form the lower mechanism. Two mathematical models based on geometric approaches are derived for the mechanisms. In order to reach a workspace fitted to that of human leg, an optimization process is performed on the mechanism. Due to the complexity of the whole model's workspace, the optimization process is done on the upper mechanism to reach its maximum workspace. Based on the ratios between thigh and calf dimensions, the lower mechanism's design parameters are obtained, and its workspace is verified to be optimal. Afterwards, a simple geometric calculation of the whole mechanism is done and compared with the results of workspace observation using MediaPipe. A brief simulation is done on the upper mechanism in two different movements in order to select suitable actuators based on the required forces. Finally, forward kinematics problem of the mechanism is solved and validated by performing simulations. © 2023 IEEE.

关键词： Actuators

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robotic Sorting of mechanical and Electrical Parts: An Autonomous Vision-Based Approach in a Practical Case Study 10

Robotic Sorting of Mechanical and Electrical Parts: An Auton...

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10th International Conference on Control, Instrumentation and Automation, ICCIA 2024

作者： Yousefi, Mohammad Dalvand, Mahdi Khomami, Navid Asadi Masouleh, Mehdi Tale Yazdi, Mohammad Reza Haeri University of Tehran Human and Robot Interaction Lab. School of Mechanical Engineering Tehran Iran University of Tehran Human and Robot Interaction Lab. School of Electrical and Computer Engineering Tehran Iran University of Tehran School of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798331509972

In today's industrial landscape, automation has become increasingly vital, particularly in the deployment of robots for tasks such as sorting machine components. The use of robotic systems enhances process accuracy and speed, resulting in significant cost reductions and improved productivity compared to manual labor. This paper aims to design and develop an automated sorting system for various types of mechanical and electrical parts, utilizing image processing and machine vision algorithms with a Delta parallel robot equipped with a two-finger gripper. The target mechanical and electrical parts in this study are screws, nuts, metal washers, rubber washers, retaining rings, rectangular keys, wall plugs, resistors, potentiometers, capacitors, batteries, ICs, and LEDs. The YOLOv3 algorithm and Adaptive Thresholding method are employed to detect and distinguish objects from the background, and size measurement is achieved with the help of a custom marker with known dimensions. In this study, transfer learning based on pre-Trained weights of YOLOv3 for the COCO dataset is applied. The proposed system attains a final mean Average Precision (mAP@0.5) value exceeding 0.95 for part detection using YOLOv3. Additionally, it demonstrates an overall pick-And-place success rate exceeding 90%. © 2024 IEEE.

关键词： Grippers

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Multisource Domain Metalearning Network for Battery State-of-Health Estimation under Multitarget Working Conditions

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IEEE Transactions on Power Electronics 2025年第7期40卷 9786-9799页

作者： Miao, Mengqi Xiao, Chaoang Yu, Jianbo Tongji University School of Mechanical Engineering Shanghai201804 China Shanghai Key Laboratory of Wearable Robotics and Human-Machine Interaction Shanghai201804 China

State of health (SOH) estimation is important in battery health prognostics. The discrepancy in working conditions gives rise to the phenomenon of domain shift, which presents a significant obstacle to the accurate estimation of battery SOH. Domain adaptation (DA) has been widely used to solve the domain shift problem in battery SOH estimation by minimizing the distribution discrepancy between different domains. However, the multitarget domain shift problem is not be addressed well for existing methods. Most existing DAs only consider a single target domain, which means that the model needs to be retrained when new scenarios emerge, which differ from the original target working condition. In this article, multisource domain metalearning network (MSDMLN) is proposed for battery SOH estimation under multiple target working conditions. A novel metalearning method, multisource domain metalearning (MSDML) strategy is developed for enhancing the generalization of the network by diversifying battery health degradation features based on meta fusion block. Empirical mode decomposition-densely connected recurrent-convolution network is developed to extract global degradation tendency and local fluctuation features of Li-ion batteries. The effectiveness of MSDMLN is verified on the combined Li-ion battery dataset. The results demonstrate that MSDMLN achieved low mean absolute error (i.e., 0.0474) and normalized root mean square error (i.e., 0.2187) for three different target operating conditions, which is better than other state-of-the-art methods. This illustrates the outperformance of MSDMLN in generalizing the estimation of battery SOH under multitarget working conditions, due to the integration of MSDML and the meta fusion block. © 1986-2012 IEEE.

关键词： Electronic health record

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