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arXiv 2020年

作者： Nagpal, Raghav Krishnan, Achyuthan Unni Yu, Hanshen Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States Mechanical Engineering Department Worcester Polytechnic Institute WorcesterMA01609 United States

—Robotic grasping is a crucial area of research as it can result in the acceleration of the automation of several Industries utilizing robots ranging from manufacturing to healthcare. Reinforcement learning is the field of study where an agent learns a policy to execute an action by exploring and exploiting rewards from an environment. Reinforcement learning can thus be used by the agent to learn how to execute a certain task, in our case grasping an object. We have used the Pick and Place environment provided by OpenAI’s Gym to engineer rewards. Hindsight Experience Replay (HER) has shown promising results with problems having a sparse reward. In the default configuration of the OpenAI baseline and environment the reward function is calculated using the distance between the target location and the robot end-effector. By weighting the cost based on the distance of the end-effector from the goal in the x,y and z-axes we were able to almost halve the learning time compared to the baselines provided by OpenAI, an intuitive strategy that further reduced learning time. In this project, we were also able to introduce certain user desired trajectories in the learnt policies (city-block / Manhattan trajectories). This helps us understand that by engineering the rewards we can tune the agent to learn policies in a certain way even if it might not be the most optimal but is the desired manner. Copyright © 2020, The Authors. All rights reserved.

关键词： End effectors

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A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and Automotive Radars

arXiv

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arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh Graduate Degree Program of Robotics National Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan

Existing radar sensors can be classified into automotive and scanning radars. While most radar odometry (RO) methods are only designed for a specific type of radar, our RO method adapts to both scanning and automotive radars. Our RO is simple yet effective, where the pipeline consists of thresholding, probabilistic submap building, and an NDT-based radar scan matching. The proposed RO has been tested on two public radar datasets: the Oxford Radar RobotCar dataset and the nuScenes dataset, which provide scanning and automotive radar data respectively. The results show that our approach surpasses state-of-the-art RO using either automotive or scanning radar by reducing translational error by 51% and 30%, respectively, and rotational error by 17% and 29%, respectively. Besides, we show that our RO achieves centimeter-level accuracy as lidar odometry, and automotive and scanning RO have similar accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

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M2FN: Multi-step modality fusion for advertisement image assessment

arXiv

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arXiv 2021年

作者： Park, Kyung-Wha Ha, Jung-Woo Lee, JungHoon Kwon, Sunyoung Kim, Kyung-Min Zhang, Byoung-Tak Interdisciplinary Program in Neuroscience Seoul National University Korea Republic of NAVER AI LAB NAVER CLOVA Statistics and Actuarial Science Soongsil University Korea Republic of School of Biomedical Convergence Engineering Pusan National University Korea Republic of Department of Computer Science and Engineering Seoul National University Korea Republic of Surromind Robotics

Assessing advertisements, specifically on the basis of user preferences and ad quality, is crucial to the marketing industry. Although recent studies have attempted to use deep neural networks for this purpose, these studies have not utilized image-related auxiliary attributes, which include embedded text frequently found in ad images. We, therefore, investigated the influence of these attributes on ad image preferences. First, we analyzed large-scale real-world ad log data and, based on our findings, proposed a novel multi-step modality fusion network (M2FN) that determines advertising images likely to appeal to user preferences. Our method utilizes auxiliary attributes through multiple steps in the network, which include conditional batch normalization-based low-level fusion and attention-based high-level fusion. We verified M2FN on the AVA dataset, which is widely used for aesthetic image assessment, and then demonstrated that M2FN can achieve state-of-the-art performance in preference prediction using a real-world ad dataset with rich auxiliary attributes. © 2021, CC BY-NC-SA.

关键词： Marketing

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Autonomous fertilizer mixer through the Internet of Things (IoT)

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Materials Today: Proceedings 2023年 81卷 295-301页

作者： Abdul Hadi Ishak Sami Salama Hussen Hajjaj Kisheen Rao Gsangaya Mohamed Thariq Hameed Sultan Mohd Fazly Mail Lee Seng Hua Department of Mechanical Engineering Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Centre for Advanced Mechatronics and Robotics (CaMaRo) Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Laboratory of Biocomposite Technology Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia Department of Aerospace Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia Aerospace Malaysia Innovation Centre (944741-A) Prime Minister’s Department MIGHT Partnership Hub Jalan Impact 63000 Cyberjaya Selangor Darul Ehsan Malaysia Farm Mechanization Program Engineering Research Centre Malaysian Agricultural Research and Development Institute (MARDI) 43400 Serdang Selangor Darul Ehsan Malaysia Laboratory of Biopolymer and Derivatives Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia

Organic fertilizers have been used since the dawn of mankind to improve soil fertility and promote crop growth. However, the process of preparing organic fertilizers for use in agricultural activities is a labour-intensive and time-consuming procedure. Thus, in order to reduce labour costs and improve the efficiency of organic fertilizer preparation, automated organic fertilizer mixers were developed. For this research work, an improved organic fertilizer mixer based on the Internet of Things (IoT) technology capable of monitoring the status of fertilizer production remotely and providing updates and alerts to workers was developed. The aim of this work was to further reduce labour workload and costs, thus increasing efficiency of the organic fertilizer mixing process. In order to accommodate the IoT monitoring system, several modifications and design changes were carried out on the prototype of an automated organic fertilizer mixer. Tests conducted on the prototype unit showed that it performs as required. The IoT monitoring system successfully captures and uploads information on the weight of agricultural waste mixture in the storage drum to the IoT platform. This information can then be used to alert workers on when to add more agricultural waste material to the mixture or remove the processed organic fertilizer. Furthermore, an overall operational cost comparison of different organic fertilizer production methods showed that the automated organic fertilizer prototype provides operational cost savings of over 5 times when compared to current automated systems. Future work includes further automation to the agricultural waste filling and organic fertilizer removal process.

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Redesigning dispenser component to enhance performance crop-dusting agriculture drones

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Materials Today: Proceedings 2023年 81卷 166-172页

作者： Rajvin Subramaniam Sami Salama Hussen Hajjaj Kisheen Rao Gsangaya Mohamed Thariq Hameed Sultan Mohd Fazly Mail Lee Seng Hua Department of Mechanical Engineering Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Centre for Advanced Mechatronics and Robotics (CaMaRo) Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Laboratory of Biocomposite Technology Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia Department of Aerospace Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia Aerospace Malaysia Innovation Centre (944741-A) Prime Minister’s Department MIGHT Partnership Hub Jalan Impact 63000 Cyberjaya Selangor Darul Ehsan Malaysia Farm Mechanization Program Engineering Research Centre Malaysian Agricultural Research and Development Institute (MARDI) 43400 Serdang Selangor Darul Ehsan Malaysia Laboratory of Biopolymer and Derivatives Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia

Agricultural drones are Unmanned Aerial Vehicles (UAVs) applied to farming in order to help increase crop production and improve farm efficiency. Crop-dusting drones are able to spray powdered fertilizer, pesticide, or insecticide on crops from the air, resulting in reduced costs and increased efficiency compared to traditional methods. The objective of this research work was to improve and enhance the performance of the crop-dusting process using agricultural drones. This research paper details the development of an improved storage container design and stabilized release mechanism for crop-dusting. To stabilise the release of payload when the drone is moving or swaying in the air, a gimbal mechanism was added to the release mechanism in which weights were used to produce constant downward force which balances the mechanism. Tests conducted on the prototype system showed that it performs as required. The stabilization tests show an improvement in accuracy of granule spread when using the stabilized release mechanism developed in this research work. As such, the wastage of fertilizers and pesticides can be reduced. The prototype system was also found to much more capable at carrying heavier loads for a longer period of time compared to current designs. Thus, using the prototype system developed for this research work, the size of storage container as well as the weight of fertilizer or pesticide granule payloads can be increased.

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Design and development of a robot for spraying fertilizers and pesticides for agriculture

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Materials Today: Proceedings 2023年 81卷 242-248页

作者： Afif Shazwan Abdul Ghafar Sami Salama Hussen Hajjaj Kisheen Rao Gsangaya Mohamed Thariq Hameed Sultan Mohd Fazly Mail Lee Seng Hua Department of Mechanical Engineering Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Centre for Advanced Mechatronics and Robotics (CaMaRo) Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional Jalan IKRAM-UNITEN 43000 Kajang Selangor Darul Ehsan Malaysia Laboratory of Biocomposite Technology Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia Department of Aerospace Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia Aerospace Malaysia Innovation Centre (944741-A) Prime Minister’s Department MIGHT Partnership Hub Jalan Impact 63000 Cyberjaya Selangor Darul Ehsan Malaysia Farm Mechanization Program Engineering Research Centre Malaysian Agricultural Research and Development Institute (MARDI) 43400 Serdang Selangor Darul Ehsan Malaysia Laboratory of Biopolymer and Derivatives Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia 43400 UPM Serdang Selangor Darul Ehsan Malaysia

The agriculture industry is one that is highly resource- and labour-intensive. As such, farmers are increasingly turning to technology and automation to address this issue. However, agricultural robots are far too complicated, slow, and costly to be made publicly available. As a result, the agriculture sector still lags behind in integrating modern technologies. This research paper details the development of a low-cost agricultural robot for spraying fertilizers and pesticides in agriculture fields as well as for general crop monitoring. The prototype system is a two-wheeled robot that consists of a mobile base, a spraying mechanism, a wireless controller for controlling the robot movement, and a camera for crop health and growth monitoring as well as detecting the presence of pests in the agriculture field. Tests conducted on the prototype system show that while the productivity of the robot in terms of crop coverage is slightly lower than a human worker, the labour cost savings afforded by the agricultural robot prototype is much greater as it functions completely in an autonomous mode and only requires the operator to control the robot when placing it at the start of the crop path. Furthermore, the prototype system also provides greater resource savings and reduction in the contamination of underground water sources due to leeching process, thus achieving precision agriculture goals. Lastly, the excellent battery life of the prototype system ensures that there will be no increase in the operation times and reduction in the efficiency of the fertilizer and pesticide spraying process due to the recharging times when replacing human workers. Future recommendations include making the agricultural robot fully autonomous, using either a rail- or line-following system, to further reduce the labour requirements and costs.

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Design and fabrication of an agricultural robot for crop seeding

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Materials Today: Proceedings 2023年 81卷 283-289页

作者： Hussain Nor Azmi Sami Salama Hussen Hajjaj Kisheen Rao Gsangaya Mohamed Thariq Hameed Sultan Mohd Fazly Mail Lee Seng Hua Department of Mechanical Engineering Universiti Tenaga Nasional Jalan IKRAM-UNITEN Kajang Selangor Darul Ehsan 43000 Malaysia Centre for Advanced Mechatronics and Robotics (CaMaRo) Universiti Tenaga Nasional Jalan IKRAM-UNITEN Kajang Selangor Darul Ehsan 43000 Malaysia Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional Jalan IKRAM-UNITEN Kajang Selangor Darul Ehsan 43000 Malaysia Laboratory of Biocomposite Technology Institute of Trop‘ical Forestry and Forest Products (INTROP) Universiti Putra Malaysia UPM Serdang Selangor Darul Ehsan 43400 Malaysia Department of Aerospace Engineering Faculty of Engineering Universiti Putra Malaysia UPM Serdang Selangor Darul Ehsan 43400 Malaysia Aerospace Malaysia Innovation Centre (944741-A) Prime Minister’s Department MIGHT Partnership Hub Jalan Impact Cyberjaya Selangor Darul Ehsan 63000 Malaysia Farm Mechanization Program Engineering Research Centre Malaysian Agricultural Research and Development Institute (MARDI) Serdang Selangor Darul Ehsan 43400 Malaysia Laboratory of Biopolymer and Derivatives Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia Serdang Selangor Darul Ehsan 43400 Malaysia

Crop seeding is a time-consuming and tedious activity for farmers and is only exacerbated in large agriculture fields. Manually sowing seeds by hand is a highly inefficient process that requires a lot of human effort and can lead to health concerns for farmers, while spreading seedlings using tractors results in a high wastage of seedlings. This research paper describes the development of a low-cost agricultural robot for crop seeding. The prototype system consists of two parts, namely a mobile base for robot movement and a seeding mechanism attached to the mobile base for crop seeding application. The mobile base has a four-wheel design to ease movement on uneven terrains, while the seeding mechanism uses the concept of a crank-slider to continuously inject seedlings into the ground. Crop seeding tests show that the robot is able to sow 138 seedlings in 5 min, with an accuracy of 92%, compared to 102 seedlings by human workers. This demonstrates an increase in the crop seeding efficiency of over 35%. As for the battery life test, it was determined that the robot can function for up to 4 h on a single charge. Thus, there will not be an increase in the operation time and reduction in the efficiency of the crop seeding process due to the recharging times when human workers are replaced with the prototype system. The recharging duration for the robot power supply is 1.5 h. While the prototype system has successfully achieved its objective of reducing human interference, labour requirement, and the overall operating costs in the field of agriculture for crop seeding process, by making the robot fully autonomous, using either a rail- or line-following system, labour costs can be further reduced as an operator is not required to manually steer the robot to each seeding path.

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Three-Dimensional Visual Mapping of Underwater Ship Hull Surface using View-based Piecewise-Planar Measurements

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IFAC-PapersOnLine 2019年第21期52卷 384-389页

作者： Seonghun Hong Jinwhan Kim Robotics Program KAIST Daejeon Korea Department of Mechanical Engineering KAIST Daejeon Korea

Visual inspection of underwater ship hulls using unmanned underwater vehicles needs to be conducted at very close range to the target surface because of the limited visibility conditions in underwater environments due to light attenuation, scattering, and turbidity. These environmental challenges result in ineffective photometric and geometric information in hull surface images, and thus, the performance of conventional 3D reconstruction techniques is often not satisfactory. This paper presents a visual mapping method for 3D reconstruction of underwater ship hull surface using a monocular camera as a primary mapping sensor. The main idea of the proposed approach is to model the moderately curved hull surface as a combination of piecewise-planar panels, and to generate a global map by aligning the images in a 2D reference frame and correcting them appropriately to reflect the information of perspective projections of the 3D panels. Experimental results are shown to demonstrate the feasibility of the proposed method using a dataset obtained in a field experiment with a full-scale ship in a real sea environment.

关键词： visual mapping 3D reconstruction computer vision autonomous underwater vehicle visual inspection

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OriSnake: Design, Fabrication, and Experimental Analysis of a 3-D Origami Snake Robot

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IEEE robotics and Automation Letters 2018年第3期3卷 1993-1999页

作者： Luo, Ming Yan, Ruibo Wan, Zhenyu Qin, Yun Santoso, Junius Skorina, Erik H. Onal, Cagdas D. Mechanical Engineering Department and Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States

Snake robots offer a useful and unique mobility platform for search-and-rescue applications. However, existing prototypes made of rigid links and joints are hampered by a lack of flexibility that limits their utility in highly cluttered, maze-like environments, and their heavy weight limits their energy-efficiency and performance in three-dimensional (3-D) tasks. To address these challenges, this letter presents a new approach using cylindrical, origami continuum modules driven by internal cables and electric motors, as well as a local feedback control system on each module. Thus, we can distribute actuation, sensing, and control for highly scalable soft robotic continuum origami systems. Using this approach, we develop a 3-D origami robotic snake that is able to locomote using lateral undulation and sidewinding gaits similar to those used by biological snakes. The proposed snake robot is a continuously deformable, lightweight, modular, and low cost robotic system made of a folded thin plastic body. We detail the design, fabrication, and control of this first 3-D origami robotic snake prototype, focusing on the analysis of locomotion parameters for each gait. We experimentally search for the optimal parameters for both types of locomotion, with maximum speeds characterized as 40.5 mm/s (0.1 body-lengths per second) for lateral undulation and 35 mm/s (0.09 body-lengths per second) for sidewinding locomotion. © 2016 IEEE.

关键词： Fabrication

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Automatic petrol and diesel engine sound identification based on machine learning approaches 1

Automatic petrol and diesel engine sound identification base...

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1st International Conference on Automotive, Manufacturing, and Mechanical engineering, IC-AMME 2018

作者： Frederick, Halim Winda, Astuti Solihin, Mahmud Iwan Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia Faculty of Engineering Technology and Built Environment UCSI University Cheras Kuala Lumpur56000 Malaysia

Petrol and diesel engine have a significantly different way to convert chemical energy into mechanical energy. In this work, the intelligent system approach is used to automatically identify the type of engine based on the sound of the engine. The combination of signal processing and machine learning technique for automatic petrol and diesel engine sound identification is presented in this work. After a signal preprocessing step of the engine sound, a Fast Fourier Transform (FFT)-based frequency characteristic modelling technique is applied as the feature extraction method. The resulting features extracted from the sound signal, in the form of frequency in the FFT matrix, are used as the inputs for the machine learning, the Support Vector Machine (SVM), step of the proposed approach. The experiment of FFT with SVM-based diesel and petrol engine sound identification has been carried out. The results show that the proposed approach produces a good accuracy in the relatively short training time. Experimental results show the training and testing accuracy of 100 % and 100 % respectively. They confirm the effectiveness of the proposed intelligent automatic diesel and petrol engine sound identification based on Fast Fourier Transform (FFT) and Support Vector Machines (SVMs). © 2019 The Authors, published by EDP Sciences.

关键词： Support vector machines

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