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IEEE International Conference on robotics and Automation (ICRA)

作者： Wesley Roozing Glenn Roozing Robotics & Mechatronics (RaM) Group University of Twente The Netherlands Auto Elect B.V. The Netherlands

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Recent trends in robotic actuation have highlighted the need for low cost, high performance, and efficient gearing. We present an experimental study comparing pinwheel and non-pinwheel designs of cycloidal gearing. The open source designs are 3D-printable, combined with off-the-shelf components, achieving a high performance-to-cost ratio. Extensive experimental data is presented, that compares two prototypes on run-in behaviour and a number of quantitative metrics including transmission error, play, friction, and stiffness. Furthermore, we assess overall actuator performance through position control experiments, and a 10-hour endurance test. The results show strong performance characteristics, and crucially, suggest that non-pinwheel designs of cycloidal gearing can be a lower complexity and cost alternative to classical pinwheel designs, while offering similar performance.

关键词： Measurement Actuators Costs Friction Prototypes Position control Market research

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Adaptive Random Field Scanning System 14

Adaptive Random Field Scanning System

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14th International Conference on Advanced Computer Information Technologies, ACIT 2024

作者： Ivakhiv, Orest Nakonechnyi, Yurii Viter, Oleksandr Nakonechnyi, Markiyan Deyneka, Rostyslav Lviv Polytechnic National University Intelligent Mechatronics and Robotics Department Lviv Ukraine Lviv Polytechnic National University Information Security Department Lviv Ukraine Lviv Polytechnic National University Computarized Automation Systems Department Lviv Ukraine

There are possibilities of the random field characteristics study analyzed. There is the polynomial adaptive principle for system design used. The expression makes it possible to evaluate the main characteristics of t... 详细信息

ISBN: (纸本)9798350350036

关键词： adaptation compressing field random system

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DeepRice: A deep learning and deep feature based classification of Rice leaf disease subtypes

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Artificial Intelligence in Agriculture 2024年第1期11卷 34-49页

作者： P.Isaac Ritharson Kumudha Raimond X.Anitha Mary Jennifer Eunice Robert Andrew J Department of CSE Karunya Institute of Technology and Sciences CoimbatoreTamilnaduIndia Department of Robotics Engineering Karunya Institute of Technology and SciencesCoimbatoreIndia Department of Mechatronics Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipalKarnataka 576104India Department of Computer Science and Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipalKarnataka 576104India

Rice stands as a crucial staple food globally,with its enduring sustainability hinging on the prompt detection of rice leaf ***,efficiently detecting diseases when they have already occurred holds paramount importance for solving the cost of manual visual identification and chemical *** the recent past,the identification of leaf pathologies in crops predominantly relies on manual methods using specialized equipment,which proves to be time-consuming and *** study offers a remedy by harnessing Deep Learning(DL)and transfer learning techniques to accurately identify and classify rice leaf diseases.A comprehensive dataset comprising 5932 self-generated images of rice leaves was assembled along with the benchmark datasets,categorized into 9 classes irrespective of the extent of disease spread across the *** classes encompass diverse states including healthy leaves,mild and severe blight,mild and severe tungro,mild and severe blast,as well as mild and severe brown *** meticulous manual labelling and dataset segmentation,which was validated by horticulture experts,data augmentation strategies were implemented to amplify the number of *** datasets were subjected to evaluation using the proposed tailored Convolutional Neural Networks *** performance are scrutinized in conjunction with alternative transfer learning approaches like VGG16,Xception,ResNet50,DenseNet121,Inception ResnetV2,and Inception *** effectiveness of the proposed custom VGG16 model was gauged by its capacity to generalize to unseen images,yielding an exceptional accuracy of 99.94%,surpassing the benchmarks set by existing state-of-the-art ***,the layer wise feature extraction is also visualized as the interpretable AI.

关键词： Rice leaf disease Deep learning CNN Crop yield Agriculture Food security

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Development of a Throwbot with Shock Absorption Structure

Development of a Throwbot with Shock Absorption Structure

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

作者： Jaeyeong Keum Jaemin Kim Changgi Lee Seunghyun Lim Insung Ju Dongwon Yun Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu South Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this study, a throwing robot equipped with an shock absorbing structure, utilizing paired-Cross Flexural Hinge (p-CFH) and an airbag, was fabricated and validated to assess the effectiveness of its impact absorption mechanism. This robot was developed in anticipation of situations where direct human intervention for life rescue would be challenging. Throwing robots can be broadly categorized into ball type, wheel type, and hybrid type. The hybrid type combines the advantages of both: the ease of throwing from ball type, due to its low air resistance coefficient, and the versatile mobility of the wheel type in diverse environments. However, hybrid type throwing robots are more vulnerable to external impacts due to the complexity of their internal structure, resulting in a lower maximum drop height compared to wheel type *** address these challenges, this research proposes a the Throwbot that combines the easy throwing capability of ball type with the obstacle overcoming ability of the wheel type, while also addressing the low free fall height drawback inherent in hybrid types. To achieve this, we developed a Throwbot with a ball to wheel transform structure, p-CFH mechanism, and airbag based impact absorption system. Additionally, materials were selected based on simulation results to refine the Throw-bot. The performance of the proposed robot was evaluated through various assessments, including free fall experiments and obstacle overcoming tests. Through this research, the proposed Throwbot effectively addresses the shortcomings of existing throwing robots, establishing a novel approach to throwing robot design.

关键词： Absorption Electric shock Simulation Wheels Transforms Reconnaissance Mobile robots Robots Intelligent robots Immune system

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Optimization of Polymeric Microneedle Electrode for High-Quality EMG recording

Optimization of Polymeric Microneedle Electrode for High-Qua...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Jinwoong Jeong Yongwoo Kim Sanghoon Lee Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

This paper proposes the optimization of polyimide microneedle electrode using a 3D print double molding fabrication. Various shapes (circle, triangle, square, star, and hexagon) of microneedles are investigated by changing printing angles and double molding process. Aspect ratio, insertion force, and break point of the fabricated microneedles are investigated to maximize penetration capacity. Also, muscle signals were obtained using optimized microneedle electrodes to distinguish hand gesture.

关键词： Electrodes Fabrication Shape Force Stars Polyimides Muscles Three-dimensional printing Recording Optimization

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Simulation of Underwater Robot Autonomous Motion Along Predetermined Straight Path 16th

Simulation of Underwater Robot Autonomous Motion Along Prede...

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16th International Conference on Electromechanics and robotics "Zavalishin’s Readings", ERZR 2021

作者： Safarov, Jamil Jatsun, Sergey Yatsun, Andrey Knyazev, Sergey Department of Mechanics Mechatronics and Robotics South-West State University 94 50 Let Oktyabrya Str. Kursk305040 Russia

ISBN: (纸本)9789811628139

The development of systems for automated water monitoring for quality control in reservoirs (SAWM) allows the prompt real-time assessment of the environmental situation at various points in the monitoring area. One of the main steps preceding the study of the water quality is sampling. The stationary character of such pollution analyzers makes it practically impossible to provide control at various sites of the monitoring object. In this article, there is considered a problem of specified rectilinear motion separation, in definition of the miniature unmanned underwater vehicles (MUUV) "specified point" desired position and perturbed motion resulting from an external disturbance. The research objectives are the development of mathematical models describing the process of MUUV trajectory generation, as well as the development of a mathematical model of the MUUV system. The development of a motion control strategy in the study of water quality is carried out to organize the sampling process. A mathematical model which describes perturbed motion is proposed, and a method for the synthesis of the parameters of control system regulator based on the decomposition of the MUUV motion equations and transient process is developed. Mathematical models of the force factors acting on the MUUV were developed in view of external pulse disturbances. Mathematical model of autonomous space motion of miniature unmanned underwater vehicles (MUUV) is presented. The method of regulator parameters definition by use of roots approach is considered. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Water quality

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GripFlexer: Development of hybrid gripper with a novel shape that can perform in narrow spaces

GripFlexer: Development of hybrid gripper with a novel shape...

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

作者： Donghyun Kim Sunghyun Choi Bongsub Song Jinhyeok Song Jingon Yoon Dongwon Yun Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu South Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In recent years, the role of robots across industries has become increasingly diverse, and they are now required to perform complex missions beyond simple repetitive tasks. However, robots used in confined spaces that humans cannot reach or in disaster field missions have challenges in performing various tasks due to their small size. In this study, we developed a compact hybrid gripper that fuses a multi-finger gripper and a jamming gripper to perform various tasks in a confined environment. Such a hybrid gripper can have both the strengths of a multi finger gripper that can perform various tasks and a jamming gripper that can effectively handle irregular small objects. In this study, we developed a hybrid gripper "GripFlexer" based on theoretical analysis and confirmed its performance through experiments by taking the task of turning a circular doorknob, which is one of the most difficult tasks in disaster sites, as the final target task. We also confirmed that the two grippers of GripFlexer can interact by showing performance improvement effects when two grippers are operated simultaneously.

关键词： Torque Service robots Shape Disasters Space missions Force Production Turning Grippers Jamming

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ReSyRIS - A Real-Synthetic Rock Instance Segmentation Dataset for Training and Benchmarking

ReSyRIS - A Real-Synthetic Rock Instance Segmentation Datase...

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IEEE Conference on Aerospace

作者： Wout Boerdijk Marcus G. Müller Maximilian Durner Rudolph Triebel German Aerospace Center (DLR) Institute of Robotics and Mechatronics Weßling Germany

The exploration of our solar system for understanding its creation and investigating potential chances of life on other celestial bodies is a fundamental drive of human mankind. After early telescope-based observation, Apollo 11 was the first space mission able to collect samples on the lunar surface and take them back to earth for analysis. Especially in recent years this trend accelerates again, and many successors were (or are in the process of being) launched into space for extra-terrestrial sample extraction. Yet, the abundance of potential failures makes these missions extremely challenging. For operations aimed at deeper parts of the solar system, the operational working distance extends even further, and communication delay and limited bandwidth increase complexity. Consequently, sample extraction missions are designed to be more autonomous in order to carry out large parts without human intervention. One specific sub-task particularly suitable for automation is the identification of relevant extraction candidates. While there exists several approaches for rock sample identification, there are often limiting factors in the form of applicable training data, lack of suitable annotations of the very same, and unclear performance of the algorithms in extra-terrestrial environments because of inadequate test data. To address these issues, we present ReSyRIS (Real-Synthetic Rock Instance Segmentation Dataset), which consists of real-world images together with their manually created synthetic counterpart. The real-world part is collected in a quasi-extra-terrestrial environment on Mt. Etna in Sicily, and focuses recordings of several rock sample sites. Every scene is re-created in OAISYS, a Blender-based data generation pipeline for unstructured outdoor environments, for which the required meshes and textures are extracted from the volcano site. This allows not only precise re-construction of the scenes in a synthetic environment, but also generation of highly real

关键词： Annotations Neural networks Training data Benchmark testing Rocks Volcanoes Solar system

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Criteria for Discussing the Results of Experimental Studies of Plastic and Brittle Materials

Criteria for Discussing the Results of Experimental Studies ...

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International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： T. B. Duishenaliev A. I. Mozgunova T. N. Dogadina V. E. Tsoy Department of Robotics Mechatronics Dynamics and Machine Strength National Research University “MPEI” Moscow Russian Federation

In experiments on axial tension and compression of solid cylinders, only some components of the deformation can be measured instrumentally, and the stress components cannot be directly measured at all. In order to discuss the test results of ductile and brittle materials, we propose to use a new equation (criterion). It is obtained by integrating the differential equation of axial motion, which uses the generalized Hooke's law and boundary conditions on the base and side surface of the cylindrical sample. The equation relates the load to axial and circumferential deformations and describes the experimental data at all levels of deformation of materials at the same values of the Lame constants.

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Estimator-Coupled Reinforcement Learning for Robust Purely Tactile In-Hand Manipulation

Estimator-Coupled Reinforcement Learning for Robust Purely T...

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IEEE-RAS International Conference on Humanoid Robots

作者： Lennart Röstel Johannes Pitz Leon Sievers Berthold Bäuml DLR Institute of Robotics and Mechatronics Technical University of Munich and Deggendorf Institute of Technology

This paper identifies and addresses the problems with naively combining (reinforcement) learning-based controllers and state estimators for robotic in-hand manipulation. Specifically, we tackle the challenging task of purely tactile, goal-conditioned, dextrous in-hand reorientation with the hand pointing downwards. Due to the limited sensing available, many control strategies that are feasible in simulation when having full knowledge of the object's state do not allow for accurate state estimation. Hence, separately training the controller and the estimator and combining the two at test time leads to poor performance. We solve this problem by coupling the control policy to the state estimator already during training in simulation. This approach leads to more robust state estimation and overall higher performance on the task while maintaining an interpretability advantage over end-to-end policy learning. With our GPU-accelerated implementation, learning from scratch takes a median training time of only 6.5 hours on a single, low-cost GPU. In simulation experiments with the DLR-Hand II and for four significantly different object shapes, we provide an in-depth analysis of the performance of our approach. We demonstrate the successful sim2real transfer by rotating the four objects to all 24 orientations in the $\pi/2$ discretization of SO(3), which has never been achieved for such a diverse set of shapes. Finally, our method is able to reorient a cube consecutively to in median nine goals, which was beyond the reach of previous methods in this challenging setting. (Web: https://***/dlr-tactile-manipulation)

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