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Review on polishing of atomic-level surfaces for potassium dihydrogen phosphate

Tribology International 2024年 198卷

作者： Meng, Fanning Zhang, Zhenyu Zeng, Zinuo Fan, Cheng Gu, Yang Gao, Fei Luo, Hao Wang, Jianmei Li, Guo School of Mechanical Engineering Hangzhou Dianzi University Hangzhou 310018 China State Key Laboratory of High-performance Precision Manufacturing Dalian University of Technology Dalian 116024 China College of Management Science Chengdu University of Technology Chengdu 610059 China Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electrical Engineering Soochow University Suzhou 215021 China Institute of Development for Science and Technology Hainan University Haikou 570228 China Department of Mechanical Engineering Tsinghua University Beijing 100084 China Luoyang Bearing Research Institute Co. Ltd Luoyang 471039 China Baoshan Longi Silicon Material Co. Ltd Baoshan 678315 China School of Mechanical Engineering Taiyuan University of Science and Technology Taiyuan 030024 China Research Center of Laser Fusion China Academy of Engineering Physics Mianyang 621900 China

Potassium dihydrogen phosphate (KDP) is a key material for inertial confinement fusion and nonlinear optic devices. However, KDP is soft-brittle, deliquescent and temperature-sensitive, making it become a difficult-to-process crystal. Even that, high-performance devices of KDP strictly require atomic-level surfaces, rising a challenge for ultra-precision machining. Due to the nature of deliquescence of KDP, traditional polishing methods are disabled to machine it. As a result, it is significant to summarize advanced polishing methods to achieving atomic-level surfaces of KDP. This review presents the fluid jet polishing, deliquescent polishing and chemical mechanical polishing (CMP) for KDP. It indicates that CMP with rare earth could obtain atomic-level surfaces and the lowest subsurface damages. Finally, future polishing directions on KDP are proposed and discussed. © 2024 Elsevier Ltd

关键词： Atomic surface Atomic-level polishing Chemical mechanical polishing KDP

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Deep Learning-Based Automatic Multi-Level Airway Collapse Monitoring on Obstructive Sleep Apnea Patients

arXiv

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arXiv 2024年

作者： Hsu, Ying-Chieh Liu, Stanley Yung-Chuan Huang, Chao-Jung Wu, Chi-Wei Cheng, Ren-Kai Hsu, Jane Yung-Jen Huang, Shang-Ran Cheng, Yuan-Ren Hsu, Fu-Shun Department of Biomedical Engineering National Taiwan University Taipei Taiwan Department of Otolaryngology Head and Neck Surgery Taipei Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Taipei Taiwan Tzu Chi University School of Medicine Hualien Taiwan Department of Oral & Maxillofacial Surgery Nova Southeastern University College of Dental Medicine College of Allopathic Medicine Florida United States All Vista Healthcare Center Center for AI and Advanced Robotics National Taiwan University Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Artificial Intelligence Chang Gung University College of Intelligent Computing Taoyuan Taiwan Heroic Faith Medical Science Co. Ltd. New Taipei Taiwan School of Medicine Chung Shan Medical University Taichung Taiwan Department of Internal Medicine Chung Shan Medical University Taichung Taiwan Hospital Development Affairs Office Chung Shan Medical University Hospital Taichung Taiwan

This study investigated the use of deep learning to identify multi-level upper airway collapses in obstructive sleep apnea (OSA) patients based on snoring sounds. We fi-ne-tuned ResNet-50 and Audio Spectrogram Transformer (AST) models using snoring recordings from 37 subjects undergoing drug-induced sleep endoscopy (DISE) between 2020 and 2021. Snoring sounds were labeled according to the VOTE (Velum, Orophar-ynx, Tongue Base, Epiglottis) classification, resulting in 259 V, 403 O, 77 T, 13 E, 1016 VO, 46 VT, 140 OT, 39 OE, 30 VOT, and 3150 non-snoring (N) 0.5-second clips. The models were trained for two multi-label classification tasks: identifying obstructions at V, O, T, and E levels, and identifying retropalatal (RP) and retroglossal (RG) obstruc-tions. Results showed AST slightly outperformed ResNet-50, demonstrating good abil-ity to identify V (F1-score: 0.71, MCC: 0.61, AUC: 0.89), O (F1-score: 0.80, MCC: 0.72, AUC: 0.94), and RP obstructions (F1-score: 0.86, MCC: 0.77, AUC: 0.97). However, both models struggled with T, E, and RG classifications due to limited data. Retrospective analysis of a full-night recording showed the potential to profile airway obstruction dynamics. We expect this information, combined with polysomnography and other clinical parameters, can aid clinical triage and treatment planning for OSA patients. © 2024, CC BY-SA.

关键词： Endoscopy

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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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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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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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Optimal Level of Assistance and Weight of Hip-joint Wearable Robot Considering Influences to the Human Body

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IFAC-PapersOnLine 2019年第22期52卷 13-18页

作者： Yoosuk Kim Sungwon Shin Kyoungchul Kong Dyhyun Han Autonomous Driving Development Team Hyundai Motor Group Gyeonggi-do Korea Angel Robotics Seoul Korea Mechanical Engineering Department Korea Advanced Institute of Science and Technology Daejeon Korea Mechanical Engineering Department Sogang University Seoul Korea

There have been many studies on design and control of hip-joint wearable robots, a part of which have already been commercialized. However, the clear assistance effects of the wearable robot on the human body have not been studied much yet. Although the human body dynamics may be considered in the robot design stage, it is difficult to predict the resultant after wearing the robot due to the complicated nature of human-robot interaction. Another difficulty in designing a hip-joint wearable robot is that the weight of the robot must be taken into consideration because the wearer must fully bear the whole weight of the robot. If a high performance actuator is used to provide greater assistance, the weight of the robot will inevitably increase, putting a burden on the human body. In this paper, musculoskeletal simulation is utilized to predict and analyze the effects of assistance and weight of robot on the human body. Then, the reliability of the simulation is verified through the wearable robot experiment. Furthermore, the relationship between assistance and weight of the robot is derived from the specifications of the commercial hip-joint wearable robots. As a result of the parameter study by applying this relationship, the optimal hip-joint wearable robot weight that the human can receive the best assistance effect is obtained.

关键词： Wearable Robot Weight Hip-joint Wearable Robot Musculoskeletal Simulation Metabolic Cost

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LED Visible Light Localization Based on Illuminance Analysis

LED Visible Light Localization Based on Illuminance Analysis

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Chenting Gu Xiaofeng Liu Yongsheng Ou Chao Liu Hao Tao Tianyun Shi HoHai University Nanjing China Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen China Key Laboratory of Special Robots Changzhou China Changzhou Key Laboratory of Robots and Intelligent Technology Changzhou China College of IoT Engineering Hohai University Changzhou China Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China China Ship Development and Design Center Wuhan Tian-yun Shi China Academy of Railway Sciences Corporation Limited Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

LED based positioning technology has recently become a popular choice due to the low cost, convenience for maintenance and strong adaptability to the environment. In this paper, we introduce an illuminance-distance analysis method with a rolling shutter camera, for a low-cost indoor positioning system to improve robustness in the case of insufficient LEDs. Firstly, the binary threshold method is used to decode the light signals. Then the gray value information of image is extracted to analyze the depth of LEDs, using the illuminance attenuation theorem. It provides potential solution to the position of devices with the camera by combining depth information, image and camera intrinsic. Our proposed method reduced the minimum number of LEDs observed by the camera from three to two, using only the camera. We evaluated the proposed method with real scene data and demonstrated the effectiveness of illumination-distance model based localization.

关键词： Light emitting diodes Cameras Receivers Light sources Robots Mathematical model Image sensors

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FetReg: Placental vessel segmentation and registration in fetoscopy challenge dataset

arXiv

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arXiv 2021年

作者： Bano, Sophia Casella, Alessandro Vasconcelos, Francisco Moccia, Sara Attilakos, George Wimalasundera, Ruwan David, Anna L. Paladini, Dario Deprest, Jan Mattos, Leonardo S. Stoyanov, Danail Department of Computer Science University College London London United Kingdom Department of Advanced Robotics Istituto Italiano di Tecnologia Genoa Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy BioRobotics Institute Scuola Superiore Sant’Anna Pisa Italy Fetal Medicine Unit Elizabeth Garrett Anderson Wing University College London Hospital London United Kingdom Department of Fetal and Perinatal Medicine Istituto "Giannina Gaslini" Genoa Italy Department of Development and Regeneration University Hospital Leuven Leuven Belgium EGA Institute for Women’s Health Faculty of Population Health Sciences University College London United Kingdom

Fetoscopy laser photocoagulation is a widely used procedure for the treatment of Twin-to-Twin Transfusion Syndrome (TTTS), that occur in mono-chorionic multiple pregnancies due to placental vascular anastomoses. This procedure is particularly challenging due to limited field of view, poor manoeuvrability of the fetoscope, poor visibility due to fluid turbidity, variability in light source, and unusual position of the placenta. This may lead to increased procedural time and incomplete ablation, resulting in persistent TTTS. Computer-assisted intervention may help overcome these challenges by expanding the fetoscopic field of view through video mosaicking and providing better visualization of the vessel network. However, the research and development in this domain remain limited due to unavailability of high-quality data to encode the intra- and inter-procedure variability. Through the Fetoscopic Placental Vessel Segmentation and Registration (FetReg) challenge, we present a large-scale multi-centre dataset for the development of generalized and robust semantic segmentation and video mosaicking algorithms for the fetal environment with a focus on creating drift-free mosaics from long duration fetoscopy videos. In this paper, we provide an overview of the FetReg dataset, challenge tasks, evaluation metrics and baseline methods for both segmentation and registration. Baseline methods results on the FetReg dataset shows that our dataset poses interesting challenges, which can be modelled and competed for through our crowd-sourcing initiative of the FetReg challenge. © 2021, CC BY-NC-SA.

关键词： Semantic Segmentation

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Mood Estimation as a Social Profile Predictor in an Autonomous, Multi-Session, Emotional Support Robot for Children

Mood Estimation as a Social Profile Predictor in an Autonomo...

引用

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Edwinn Gamborino Hsiu-Ping Yueh Weijane Lin Su-Ling Yeh Li-Chen Fu Center for Artificial Intelligence and Advanced Robotics National Taiwan University Taipei Taiwan Department of Psychology and the Department of Bio-Industry Communication Development National Taiwan University Taipei Taiwan Department of Library and Information Science National Taiwan University Department of Psychology Graduate Institute of Brain and Mind Sciences and the Center for Artificial Intelligence and Advanced Robotics National Taiwan University Taipei Taiwan Department of Electrical Engineering and the Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9781728126234

In this work, we created an end-to-end autonomous robotic platform to give emotional support to children in long-term, multi-session interactions. Using a mood estimation algorithm based on visual cues of the user's behaviors through their facial expressions and body posture, a multidimensional model predicts a qualitative measure of the subject's affective state. Using a novel Interactive Reinforcement Learning algorithm, the robot is able to learn over several sessions the social profile of the user, adjusting its behavior to match their preferences. Although the robot is completely autonomous, a third party can optionally provide feedback to the robot through an additional UI to accelerate its learning of the user's preferences. To validate the proposed methodology, we evaluated the impact of the robot on elementary school aged children in a long-term, multi-session interaction setting. Our findings show that using this methodology, the robot is able to learn the social profile of the users over a number of sessions, either with or without external feedback as well as maintain the user in a positive mood, as shown by the consistently positive rewards received by the robot using our proposed learning algorithm.

关键词： Robot Multisession emotional support User preferences Child Family with school age child external feedback Consumers Emotional States body position learning algorithms Facial Expression Learning

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