1,581 research outputs found

    UltraSwarm: A Further Step Towards a Flock of Miniature Helicopters

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    We describe further progress towards the development of a MAV (micro aerial vehicle) designed as an enabling tool to investigate aerial flocking. Our research focuses on the use of low cost off the shelf vehicles and sensors to enable fast prototyping and to reduce development costs. Details on the design of the embedded electronics and the modification of the chosen toy helicopter are presented, and the technique used for state estimation is described. The fusion of inertial data through an unscented Kalman filter is used to estimate the helicopter’s state, and this forms the main input to the control system. Since no detailed dynamic model of the helicopter in use is available, a method is proposed for automated system identification, and for subsequent controller design based on artificial evolution. Preliminary results obtained with a dynamic simulator of a helicopter are reported, along with some encouraging results for tackling the problem of flocking

    Penerapan SLAM Gmapping dengan Robot Operating System Menggunakan Laser Scanner pada Turtlebot

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    The manouver ability from one place to another in order to accomplish some tasks safely is a basic requirement of mobile robotics. Current robotic’s navigation systems require a ’real world’ map data, acquired by on-board sensors, to carry out simultaneous localisation and navigation (SLAM) algorithm. There are several SLAM algorithms. In this article we used SLAM gmapping using robot operating system (ROS) and laser scanner. The gmapping slam algorithm used particle filter method to localize robot pose within the environment and generate 2D occupancy grid map. The map is in gray-scale informed the free space, wall, and unexplored space. The implementation of gmapping slam conducted with turtlebot 3 from Robotics as well as 3D simulation using gazebo.

    GPM Mission's Best Practices: PERP

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    Similar to other missions, the Global Precipitation Measurement (GPM) Core Observatory's Command and Data Handling (C&DH) subsystem is critical for operations of the spacecraft. The onboard C&DH system comprises of two fully redundant boxes - a primary and a cold backup. Within each box, amongst other components, is a Single Board Computer (SBC) that hosts the flight software (FSW) system. In the event of an SBC reset, the Flight Operations Team (FOT) is poised with a lengthy task of restoring the SBC to nominal configuration. Due to the complexity of the C&DH system, this may take many days at a time to complete. The spacecraft's FSW applications are located in Electronically Erasable Programmable Read-Only Memory (EEPROM) and are copied into Random Access Memory (RAM) upon SBC initialization/reset. Each SBC has two banks of EEPROM, with each bank containing a copy of the FSW. Since launch, there have been many configuration changes to tables and applications that have been loaded into just RAM. Unfortunately, these changes are vulnerable to being wiped during a SBC initialization/reset, when the RAM is overwritten by the EEPROM. Although the EEPROM loads the default FSW configurations, the process to command non-default individual table and application changes is very cumbersome and time consuming. This consequentially increases the time until the spacecraft is back into nominal Mission Science Mode (MSM) drastically. The GPM Power-On Reset (POR) Expedited Recovery Process (PERP) Design introduces a method of consolidating commands into a single file load which the SBC can process independently of the ground - decreasing recovery time, the level of TDRS support reliance, and human error. This tested design can be implemented across many other missions that utilize a similar core Flight Executive (cFE) platform; hence providing an easy-to-follow, safe, and efficient process that can be applied across the board

    Test, Control and Monitor System maintenance plan

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    The maintenance requirements for Test, Control, and Monitor System (TCMS) and the method for satisfying these requirements prior to First Need Date (FND) of the last TCMS set are described. The method for satisfying maintenance requirements following FND of the last TCMS set will be addressed by a revision to this plan. This maintenance plan serves as the basic planning document for maintenance of this equipment by the NASA Payloads Directorate (CM) and the Payload Ground Operations Contractor (PGOC) at KSC. The terms TCMS Operations and Maintenance (O&M), Payloads Logistics, TCMS Sustaining Engineering, Payload Communications, and Integrated Network Services refer to the appropriate NASA and PGOC organization. For the duration of their contract, the Core Electronic Contractor (CEC) will provide a Set Support Team (SST). One of the primary purposes of this team is to help NASA and PGOC operate and maintain TCMS. It is assumed that SST is an integral part of TCMS O&M. The purpose of this plan is to describe the maintenance concept for TCMS hardware and system software in order to facilitate activation, transition planning, and continuing operation. When software maintenance is mentioned in this plan, it refers to maintenance of TCMS system software

    Next-Generation Pedal: Integration of Sensors in a Braking Pedal for a Full Brake-by-Wire System

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    This article presents a novel approach to designing and validating a fully electronic braking pedal, addressing the growing integration of electronics in vehicles. With the imminent rise of brake-by-wire (BBW) technology, the brake pedal requires electronification to keep pace with industry advancements. This research explores technologies and features for the next-generation pedal, including low-power consumption electronics, cost-effective sensors, active adjustable pedals, and a retractable pedal for autonomous vehicles. Furthermore, this research brings the benefits of the water injection technique (WIT) as the base for manufacturing plastic pedal brakes towards reducing cost and weight while enhancing torsional stiffness. Communication with original equipment manufacturers (OEMs) has provided valuable insights and feedback, facilitating a productive exchange of ideas. The findings include two sensor prototypes utilizing inductive technology and printed-ink gauges. Significantly, reduced power consumption was achieved in a Hall-effect sensor already in production. Additionally, a functional BBW prototype was developed and validated. This research presents an innovative approach to pedal design that aligns with current electrification trends and autonomous vehicles. It positions the braking pedal as an advanced component that has the potential to redefine industry standards. In summary, this research significantly contributes to the electronic braking pedal technology presenting the critical industry needs that have driven technical studies and progress in the field of sensors, electronics, and materials, highlighting the challenges that component manufacturers will inevitably face in the forthcoming years.This work has been partially supported by the grant “Ayudas para el desarrollo de proyectos de I+D mediante la contratación de personas doctoradas y la realización de doctorados industriales, programa BIKAINTEK 2019” by the Department of Economic Development, Sustainability, and Environment of the Basque Government. Additionally, this work has been partially supported by the Government of Spain, through the Center for the Development of Industrial Technology (CDTI) under grant agreement IDI-20200198 and by Eusko Jaularitza-Gobierno Vasco (SOC4CRIS KK-2023/00015)

    An Intelligent Algorithm for Resource Sharing and Self-Management of Wireless-IoT-Gateway

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    [EN] Internet of Things (IoT) is rapidly gaining momentum in the scenario of telecommunications. Conventional networks allow for interactivity and data exchange, but these networks have not been designed for the new features and functions of IoT devices. In this paper, an algorithm is proposed to share common recourse among Things, that is, between different types of smart appliances. This proposal is based on an IoT network with centralized management architecture, controlled by an Artificial Intelligence (AI). The AI controller uses an algorithm which based on machine learning techniques, collecting information on the network through an information protocol. Every smart thing that connects to the network is announces through a protocol message called Function and Service Discovery Protocol (DFSP) over the queued message telemetry transport protocol (MQTT). The proposed algorithm is responsible for discovering and allocating resources in the networks. As a result, using our proposed algorithm in communication system provides the outperform efficiency and availability than that used in conventional communication systems for the integrate IoT devices.This work was supported in part by the "Ministerio de Economia y Competitividad'', through the "Convocatoria 2014 Proyectos I+D - Programa Estatal de Investigacion Cientica y Tecnica de Excelencia'' in the "Subprograma Estatal de Generacion de Conocimiento'', under Grant TIN2014-57991-C3-1-P and through the "Convocatoria 2017 -Proyectos I+D+I -Programa Estatal de Investigacion, Desarrollo e Innovacion, convocatoria excelencia'' under Grant TIN2017-84802-C2-1-PGonzalez Ramirez, PL.; Taha, M.; Lloret, J.; Tomás Gironés, J. (2019). An Intelligent Algorithm for Resource Sharing and Self-Management of Wireless-IoT-Gateway. IEEE Access. 8:3159-3170. https://doi.org/10.1109/ACCESS.2019.2960508S31593170

    Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill

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    Performing endovascular medical interventions safely and efficiently requires a diverse set of skills that need to be practised in dedicated training sessions. Here, we used multimodal magnetic resonance (MR) imaging to determine the structural and functional plasticity and core skills associated with skill acquisition. A training group learned to perform a simulator-based endovascular procedure, while a control group performed a simplified version of the task; multimodal MR images were acquired before and after training. Using a well-controlled interaction design, we found strong, multimodal evidence for the role of the intraparietal sulcus (IPS) in endovascular skill acquisition that is in line with previous work implicating the structure in simple visuo-motor and mental rotation tasks. Our results provide a unique window into the multimodal nature of rapid structural and functional plasticity of the human brain while learning a multifaceted and complex clinical skill. Further, our results provide a detailed description of the plasticity process associated with endovascular skill acquisition and highlight specific facets of skills that could enhance current medical pedagogy and be useful to explicitly target during clinical resident training
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