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arXiv 2022年

作者： Stavridis, Sotiris Papageorgiou, Dimitrios Droukas, Leonidas Doulgeri, Zoe The Automation & Robotics Lab School of Electrical & Computer Engineering Aristotle University of Thessaloniki Greece

Most existing robotic harvesters utilize a unimanual approach;a single arm grasps the crop and detaches it, either via a detachment movement, or by cutting its stem with a specially designed gripper/cutter end-effector. However, such unimanual solutions cannot be applied for sensitive crops and cluttered environments like grapes and a vineyard where obstacles may occlude the stem and leave no space for the cutter's placement. In such cases, the solution would require a bimanual robot in order to visually unveil the stem and manipulate the grasped crop to create cutting affordances which is similar to the practice used by humans. In this work, a dual-arm coordinated motion control methodology for reaching a stem pre-cut state is proposed. The camera equipped arm with the cutter is reaching the stem, unveiling it as much as possible, while the second arm is moving the grasped crop towards the surrounding free-space to facilitate its stem cutting. Lab experimentation on a mock-up vine setup with a plastic grape cluster evaluates the proposed methodology, involving two UR5e robotic arms and a RealSense D415 camera. © 2022, CC BY.

关键词： Crops

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Estimation of the Raya UUV Hydrodynamic Coefficients Using OpenFOAM

Estimation of the Raya UUV Hydrodynamic Coefficients Using O...

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OCEANS

作者： João Leitão Pedro Pereira Raul Campilho Andry Pinto Centre for Robotics and Automation Systems of INESC TEC (CRAS) CIDEM School of Engineering Polytechnic of Porto (ISEP) Faculty of Engineering University of Porto (FEUP) Institute of Science and Innovation in Mechanical and Industrial Engineering (INEGI) Porto Portugal

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

Accurate dynamics modelling of Unmanned Under-water Vehicles (UUV s) is critical for optimizing mission planning, minimizing collision risks, and ensuring the successful execution of tasks in diverse underwater environments. This paper presents a structured approach to estimating the hydrodynamic coeffi-cients of UUV s. Initially, it follows a detailed methodology for estimating hydrodynamic coefficients using simple geometries, a sphere and a spheroid, using the Computational Fluid Dy-namics (CFD) software OpenFoam, and comparing the results to analytical solutions, enabling the validation of the simulations approach. Following this, the paper provides an in-depth analysis of the damping and added mass coefficients for the Raya UUV, offering valuable insights into its hydrodynamic behaviour.

关键词： Geometry Damping Analytical models Accuracy Fluids Oceans Hydrodynamics Software Planning Vehicle dynamics

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Design of Heading Adjustment System for Composite Wing UAV Based on PID Controller

Design of Heading Adjustment System for Composite Wing UAV B...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Zhiwei Niu Liying Yang Zhaoxiong Huang Han Jiang School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

This paper studies the course adjustment problem of compound wing UAV in wind field environment. Course adjustment plays a key role in the flight of UAVs, which can ensure that UAVs maintain a stable course during flight, and achieve tasks such as precise attitude control and mode switching. For this reason, this paper proposes a heading adjustment method based on PID controller, which determines the expected yaw rate through the expected roll angle, so as to optimize the input of the attitude controller. Finally, the composite wing UAV is in the windward state before the mode switching. Experimental results show that the proposed method can achieve precise heading control in crosswind conditions, and the composite wing UAV can maintain attitude stability during heading adjustment, while effectively reducing the power output during the mode switching phase.

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Deep Learning Based Neovascularization Detection in Color Fundus Photography Image 23

Deep Learning Based Neovascularization Detection in Color Fu...

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9th International Conference on Computing and Artificial Intelligence, ICCAI 2023

作者： Guo, Tianjiao Yang, Jie Yu, Qi Institute of Medical Robotics Institute of Image Processing and Pattern Recognition Department of Automation School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Shanghai China Department of Ophthalmology Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai China National Clinical Research Center for Eye Diseases Shanghai China

ISBN: (纸本)9781450399029

Diabetic retinopathy (DR) has already been one of the leading causes of vision loss. A large number of researches about deep learning-based DR screening using color retinal photography images have been proposed in recent years. However, existing works mainly concentrated on non-proliferative diabetic retinopathy (NPDR) lesions. The exploration of proliferative diabetic retinopathy (PDR) lesion, which is more serious, is still insufficient. In this paper, we explored into one typical PDR lesion named neovascularization (NV). We collected and annotated retinal images from public and private datasets to construct and release a new dataset for NV detection. Three tasks including segmentation, detection, and grading were conducted on our dataset by using a set of state-of-the-art deep learning models. The results show that introducing NV detection can benefit DR grading. However, the segmentation and detection of NV are still challenging and have considerable room for improvement. © 2023 Copyright held by the owner/author(s).

关键词： Color

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Adaptive Vector Field Histogram Plus method for local path planning under human—robot collaboration

Adaptive Vector Field Histogram Plus method for local path p...

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Youth Academic Annual Conference of Chinese Association of automation (YAC)

作者： Chuxi Fang Shiliang Shao Ting Wang Xianzhe Zhao Fengkui Cao Hai Zhao School of Computer Science And Engineering Northeastern University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

As an expanding field that caters to the needs of the elderly and people with disabilities, intelligent wheelchairs aim to enhance the efficiency and safety of individuals with disabilities. Path planning, a pivotal technology under intelligent wheelchair systems, has emerged as a focal point of scholarly exploration. This paper proposes advancements in the vector field histogram plus (VFH+) algorithm, thereby introducing the adaptive VFH+ algorithm (AVFH+). Notably, this paper redefines the calculation of obstacle density and introduces the concept of custom target point density. By dynamically modulating the threshold, we effectively resolve the problems of oscillatory paths during obstacle avoidance, thus averting the predicament of the robot. In addition, the robot's speed is adaptively adjusted based on the opening width, and the trajectory is smoothed using Bezier path planning, enabling the robot to reach the target position through a shorter collision-free and smooth path. The improved AVFH+ algorithm demonstrates excellent path planning capability through multiple simulation experiments in various map environments with different starting points and target locations. The algorithm has the ability to adapt to complex environments, accurately perceive and avoid obstacles, and exhibits significant generalization capabilities. This makes it significant in dense area path planning, providing safer and more efficient mobility solutions in areas such as smart wheelchairs, and actively contributing to the quality of life of people with disabilities. Future research could explore the consideration of dynamic obstacles and validate the performance of the algorithm in real-world environments.

关键词： Histograms Heuristic algorithms Wheelchairs People with disabilities Vectors Trajectory Safety

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Feature Detection Method of Assembly Position Based on Machine Vision

Feature Detection Method of Assembly Position Based on Machi...

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2021 International Conference on Intelligent Computing, automation and Applications, ICAA 2021

作者： Sheng, Shaojie Zhao, Qijie Xu, Kai Shanghai University School of Mechatronic Engineering and Automation Shanghai China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China

ISBN: (纸本)9781665437301

The detection of assembly station scene features is a hot research issue in the field of computer vision. Its purpose is to superimpose assembly-related information on the corresponding assembly station scene and provide intuitive online guidance to assembly operators. To this end, this paper proposes a method based on machine vision to detect assembly station scene features, and uses dimensionality reduction processing to simplify the detected high-dimensional features, and uses a bag of words model to construct a Code Book representation method of assembly station scene feature vectors. The dimensionality reduction method is used to solve the problem of the large amount of calculations directly using natural features to match the scene. © 2021 IEEE.

关键词： Computer vision

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A Novel Gas Classification Method Based on The Improved GasNet

A Novel Gas Classification Method Based on The Improved GasN...

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第43届中国控制会议

作者： Xiaolin Qin Lei Cheng Xiang Tao Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology School of Information Science and Engineering Wuhan University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Accurately and promptly identifying harmful gases in the environment can effectively prevent many accidents. Most existing pattern recognition methods are focused on addressing gas classification problems in static scenarios, but the real world is a dynamic and changing environment. Therefore, researching gas classification in continuous learning scenarios will better meet the needs of suddenly emerging gas classification tasks in real-world environments. To address this issue, an incremental learning model was introduced into gas classification, and an improved deep convolutional network was proposed for gas image feature extraction. The proposed model and other baseline methods experimented on an open-source gas dataset. The proposed model reduces knowledge loss due to catastrophic forgetting and effectively classifies the 10 gas samples in the dataset in continuous learning scenarios compared to non-incremental methods. It outperforms other baseline incremental methods by optimizing the network's shortcut connections, making the feature extraction network easier to train and improving gas classification performance. In dynamic learning scenarios, the proposed model achieved a classification accuracy of 86.30% for 10 gas *** experimental results demonstrate that the proposed method effectively mitigates catastrophic forgetting interference and completes gas classification tasks in continuous learning scenarios.

关键词： Gas classification Incremental learning Shortcut connection Catastrophic forgetting

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Design and In-Hand Analysis of a 6-Dof 3prs-Finger-Based Parallel Dexterous Hand with Bidirectional Pinching Capability

SSRN

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SSRN 2023年

作者： Zhao, Fuqun Xu, Donglai Jin, Xiaodong Ding, Xilun Guo, Sheng Xu, Kun Fang, Yuefa Department of Mechanical Engineering Beijing Jiaotong University Beijing100044 China Robotics Institute School of Mechanical Engineering and Automation Beihang University Beijing100191 China

In view of the shortcomings of the serial dexterous hand (SDH) in heavy load, precise in-hand manipulation, and bidirectional pinching capability, this paper presents a 6-DOF 3PRS-finger-based parallel dexterous hand (PDH). The PDH structure is designed, which is composed of three 3PRS parallel fingers. The pinching shape analysis is conducted to demonstrate the bidirectional pinching capability. Through the workspace analysis of the PDH pinching nine objects, the influence rule on in-hand manipulation workspace of different objects is obtained. The PDH can perform symmetrical in-hand manipulation workspace to solve the problem that almost all of humanoid dexterous hands pinch objects in a single direction. The pinching force transmission capability of the PDH is compared with that of the 3R SDH. The results show that the maximum pinching force provided by the PDH is much greater than that provided by the SDH. Bidirectional pinching experiments are carried out, which demonstrate the PDH can complete the accurate in-hand manipulation under almost frictionless conditions. The proposed PDH can provide a feasible design idea for the theoretical development and practical application of dexterous hands. © 2023, The Authors. All rights reserved.

关键词： Robotic arms

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A Novel Simulation-Based Quality Metric for Evaluating Grasps on 3D Deformable Objects

arXiv

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arXiv 2022年

作者： Le, Tran Nguyen Lundell, Jens Abu-Dakka, Fares J. Kyrki, Ville Intelligent Robotics Group Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Finland

Evaluation of grasps on deformable 3D objects is a little-studied problem, even if the applicability of rigid object grasp quality measures for deformable ones is an open question. A central issue with most quality measures is their dependence on contact points which for deformable objects depend on the deformations. This paper proposes a grasp quality measure for deformable objects that uses information about object deformation to calculate the grasp quality. Grasps are evaluated by simulating the deformations during grasping and predicting the contacts between the gripper and the grasped object. The contact information is then used as input for a new grasp quality metric to quantify the grasp quality. The approach is benchmarked against two classical rigid-body quality metrics on over 600 grasps in the Isaac gym simulation and over 50 real-world grasps. Experimental results show an average improvement of 18% in the grasp success rate for deformable objects compared to the classical rigid-body quality metrics. Copyright © 2022, The Authors. All rights reserved.

关键词： Deformation

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Hou, Muyang Lei, Zhenya Hu, Haidong Wang, Zhong Wang, Yong Xie, Le Wang, Hesheng Shanghai Jiao Tong University Department of Automation Shanghai200240 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Beijing Institute of Control Engineering Beijing100190 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant;on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A∗ which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion. © 2024 IEEE.

关键词： Trajectories

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