Our solution is a wireless technology that allows for real-time monitoring of the health of a large number of patients. In health care facilities, patient data such as pulse rate, blood pressure, temperature, and brea...
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In haptic shared control (HSC) for teleoperation, the human operator and autonomous system share control via torque on the input device. When a discrepancy exists between the human's maneuvering intent and the aut...
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Sensing is essential in human cooperative robots to realize safe and powerful operations against contact with the surrounding environment. Contact sensing has been studied for manipulators to avoid accidents caused by...
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ISBN:
(纸本)9781728177113
Sensing is essential in human cooperative robots to realize safe and powerful operations against contact with the surrounding environment. Contact sensing has been studied for manipulators to avoid accidents caused by collisions between humans and robots. Conventional research has demonstrated that contact sensing requires many sensors or has a limited measurable range. In the conventional research without sensors, pre-identified system models, such as frictional force and plant parameters, have been used to estimate the contact force. However, a high reduction ratio mechanism for achieving powerful operations hinders accurate force estimation. This study proposes a force controlsystem based on only one force/torque sensor on the base frame of the manipulator. The proposal provides an accurate estimation of the contact force and the contact position on a manipulator with a high reduction ratio mechanism. Furthermore, by using the proposal, the contact force and contact position can be detected regardless of the location where the contact force is applied. The validity of the basic principle of the proposal was confirmed in one degree of freedom system through experiments. The results show that the proposal can be controlled with a maximum error of 0.13 N.
Open user models provide affordance for a transparent user control over recommendations based on shared symbolic representation within the system. Users must build their user profile by adding these symbols and tuning...
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ISBN:
(纸本)9798400704666
Open user models provide affordance for a transparent user control over recommendations based on shared symbolic representation within the system. Users must build their user profile by adding these symbols and tuning their importance to get meaningful recommendations. Since the link between these symbols and the reference explanation is often unavailable, it can be difficult for users to understand them. These symbols are often referred to as concepts, tags, areas, topics, labels, features, or keyphrases. This study showcases an information exploration system that helps students identify potential faculty members to collaborate with. The system works by matching user and faculty profiles that contain keywords or phrases representing topics/areas of interest. Students must develop their understanding of research topics while building their profiles, which can become challenging as they add more keywords. To support students in controlling the recommendation, we introduce post hoc explanations with three levels of detail: no explanations, individual explanation for topics, and explanation of the relationships between topics. This study explores how explanation is associated with the user context / tasks and the exploration process. Our observation suggests that expertise in the field is linked to exploring fewer novel topics and seeking fewer explanations but engaging more with explanations of relationships. In addition, we found that the engagement with faculty information is moderately correlated with the use of more advanced explanations.
Motivated by the recent interest in the modernization of the traditional manufacturing facilities, this work focuses on the development of an automated warehouse where mobile manipulators autonomously navigate in the ...
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ISBN:
(纸本)9781728177113
Motivated by the recent interest in the modernization of the traditional manufacturing facilities, this work focuses on the development of an automated warehouse where mobile manipulators autonomously navigate in the environment by exploiting additional spatial information gathered by a network of fixed RGB-D sensors. In detail, a navigation approach is proposed wherein both the mobile and fixed nodes composing the system are low-cost devices characterized by limited sensing and computing capabilities. A ROS2-based proof of concept of the outlined scenario is discussed and investigated with special regard to the practical challenges and the possible limitations. The results of some preliminary tests are reported to provide an intuition on the feasibility and potentiality of the designed approach in real-world industrial scenarios.
The integration of brain-computer interface (BCI) and virtual reality (VR) technologies has fostered innovative applications in medical rehabilitation, education, and entertainment. One prominent application is the mo...
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Global navigation satellite systems readily provide accurate position information when localizing a robot outdoors. However, an analogous standard solution does not exist yet for mobile robots operating indoors. This ...
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This article takes the pollution source treatment of the ecological environment in rural construction as the research object. First, introduces the experience and reference of ecological environmental protection in ru...
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Gaming has evolved dramatically over the past few decades, with new technologies and gaming platforms emerging, providing a more immersive and interactive gaming experience for players. However, the cost of the contro...
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The proceedings contain 88 papers. The special focus in this conference is on Communications and Cyber-Physical Engineering. The topics include: An Experimental Study on Denoising the Images with Autoencoders;cotton P...
ISBN:
(纸本)9789819971367
The proceedings contain 88 papers. The special focus in this conference is on Communications and Cyber-Physical Engineering. The topics include: An Experimental Study on Denoising the Images with Autoencoders;cotton Plant Disease Detection: A Review;an Efficient Methodology for Identifying the Similarity Between Languages with Levenshtein Distance;a Traffic Prediction Model Based on Multi Stream Feature Fusion;detection and Classification of Brain Tumor Using Convolutional Neural Network;design of Wireless sensor-Based Automation system for Laboratory Using Internet of Things;design and Implementation of Booth Multiplier with Sklansky and Ling Adders;Alzheimer’s Disease Classification Using Brain MRI Based on 2D CNN and Transfer Learning;siddu: Decentralized Authorization with Zero Trust;smart Contract-Based Blockchain Technique for Logistic Shipping Management system;design of an Interline Power Flow controller Using advanced Simulation Tools;an Efficient Approach for Smart Cold Storage Management system Using IoT;detection and Monitoring of Hazards in Mining Using IoT Based Intelligent Helmet;crop Prediction Using Machine Learning Approaches;smart Campus system;NNDcn-Neural Network Based Deep Crowd Network for Crowd Count;a Voice-Assisted Walking Support for Visually Impaired People Utilizing an Wearable sensor Network;license Plate Recognition Using Artificial Neural Network Techniques;arabica Coffee Bean Grading into Specialty and Commodity Type Based on Quality Using Visual Inspection;Lung Nodule Classification and Detection Using SVM-CAD;a Sparse Code Multiple Access for 5G Radiotransmission;The Rise of AI and ML in Financial Technology: An In-depth Study of Trends and Challenges;Wireless TCP Congestion control Based on Loss Discrimination Approach Using Machine Learning.
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