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<p>In today’s world, a lot of educated decisions are made using the information collected by robots and are aided by the inferences given by the software agents which make use of the information collected by the other machines and robots. One such crucial field, where the software agents can contribute is “Pedestrian and Vehicle Traffic Monitoring”, where they can help us identify the hotspots and conflict zones like Pedestrian Crossings, Traffic Signals, Traffic jams, etc. The aim of this project will be to achieve this by using detection networks and depth networks or localisation/pose estimation networks or by building upon the existing functionalities like “peopleCounter_SSDCNet” components already present in the robocomp repository. Through this, the information provided by machines like RGB cameras can be exploited maximally to make better decisions based on the density of people and vehicles present in an area.</p>

<p>My proposal aims to create a new component that allows to store the representation of the robot’s world over time, as well as query it. For this, it is necessary to store the graph structure used to represent the knowledge of the world that the robot possesses. In RoboComp, when robots need to perform complex tasks, its behaviour is based on missions. The mission begin from an initial state and through different transitions reaches a final state, that is, the robot completes the mission. The states are represented by a graph. My proposal is to use a JSON structure to store this graph. This allows its storage as a collection of documents in MongoDB. Consequently, each document could represent a state of the robot. Also, this slot is intended to study the viability of Neo4J for this purpose, as far as I am concerned, the best option would be to use the polyglot persistence, that consists in to use the database best suited for the type of data, in our case MongoDB, and in to use the database best suited for the type of queries, in our case Neo4j. Specifically I think that Neo4j Doc Manager could be our best choice.</p>

<p>The main topic can be divided into two parts:</p> <p>+Body and hand detection: I apply the lightweight Openpose model, MediaPipe library, and the optical flow algorithm. The combination can process in real-time and with a lightweight model, so it is suitable for edge devices.</p> <p>+Gesture recognition: There are two main approaches for this problem: image-appearance-based models and pose-based models. These two are different in types of input data. The first approach's input is only images, while the second one's input is extracted poses from photos.</p> <p>+Extension: Currently, the robot can only learn the gesture from the predefined patterns, which appear in the training data. However, the training dataset is not always available for all motions. Therefore, by applying some unsupervised techniques, the robot can recognize some gestures without any supervised dataset.</p> <p>In this project: Four components will be published: BodyHandJointsDetector, ImageBaseGesture-Recognition, PoseBasedGestureRecognition, and UnsupervisedGestureRecognition. I will also code the testing client for each approach.</p>

<p>The ability of a robot to detect, grasp and manipulate objects is one of the key challenges in building an intelligent humanoid robot. For a collaborative robot, dealing with objects is a key part of its job and its ability to manipulate objects starts with the accuracy of grasping. Intelligent control of a robotic arm to manipulate objects is based on detecting the object and understanding its pose. Precise 3D poses of the objects are necessary to achieve a successful grasp on the objects. We can use the available data from the surrounding environment to recognize the objects poses. In our environment, the data provided will be RGBD frames. Recent work in Deep Learning has achieved amazing results in the problem of 3d pose estimation using RGBD data.</p> <p>In this project, we will work to integrate a pose estimation component to RoboComp using some state-of-art work in Deep Learning. The output poses will be visualized in V-REP simulator and used to drive the new Kinova Gen3 arm, in order to precisely grasp and manipulate some objects.</p>

<p>Object detection and recognition are central problems in computer vision literature and essential for a vision based library. Recent advances in Covolutional Neural Networks (CNN)s have made the detection have made the recognition problem tractable for large number of object categories that would have been very expensive with model based classification approaches. In this project I will implement state-of-art object recognition as well as object detection/localization technique for RoboComp library. The implementation will support both real images and rendered images from CAD model. The implementation will be based on CUDA library and allow user to train and test his models. Also, a caffe independent pure RoboComp based implementation for forward pass will be developed for a selected CNN. Another component based on open scene graph will designed that would allow reading of CAD models and interfacing with current RoboComp simulation framework. Selection of rich textured CAD models is an crucial for any detection algorithm. Therefore, the proposed project will accompany a dataset of cleaned and textured CAD models for 5 object categories.</p>

My project’s primary goal is to create unit tests using KUnit for the AMDGPU driver focused on the Display and Compositing Engine (DCE) 11.2, which will be tested on the GPU “RX 580”. The motivation for that comes not only to assert that the APIs work as expected, but also to keep their behavior stable across minor changes in their code, which can allow for great improvement to the code readability and maintainability. There is a great probability that KUnit will have some limitations in regards to testing GPU’s drivers’ functions, so the secondary goal will be to enhance its capabilities. It’s expected that there will be other people working with KUnit on DCN in parallel, so there will probably be some code review to be done as well. I will keep track of my weekly progress on my blog, reporting the challenges I will face and trying to create an introductory material that could help future newcomers.

<p>Implementing an EDS module to sync with EteSync, a secure, end-to-end encrypted and FLOSS sync solution that will enable GNOME/Evolution users to easily end-to-end encrypt and sync their contacts, calendars and tasks.</p>

<p>The proposal looks forward to implement features such as API auth, calendar export, review system, etc. that could make the project better and more user friendly. The proposal also looks forward to make UI/UX enhancements in the Admin Dashboard to make the process much more intuitive.</p>

While SOF has an incredibly robust and comprehensive back-end implementation, the ability for users and developers to access the features quickly and conveniently has not yet been created. This project seeks to create a GUI that allows real-time configuration and control of SOF. The important aspects of this are the creation of generic implementations that work on all current and future supported platforms, as well as keeping ease and simplicity of use as the number one priority.

<p>This project aims at providing support for automatic import of events from various event listing sites into Open Event. This import of events is useful in two ways:</p> <pre><code>1.Import events which are not already listed in Open Event. 2.Allow a user to import events – created on other sites – directly into Open Event. </code></pre>

I aim to upgrade Visdom from a single-user visualization tool into a scalable, multi-user system. Visdom currently operates on a shared global state and lacks features like user context, authentication, workspace isolation. I plan to implement a JWT-based auth system and refactor the architecture to support user-scoped state. Deliverables are multi-user system featuring isolated environments, role based access control, basic collaboration and presentation features, controlled experiment sharing.

<ul> <li>Bassa has been deployed on a single node Kubernetes cluster with good orchestration yet there is a need for a dedicated monitoring and alerting system integrated into this cluster. </li> <li>Bassa has a dedicated API server that serves the purpose of an automated download queue. Writing efficient client libraries would surely be a great use for other developers to easily integrate the automated download queue into their projects.</li> </ul>

<ul> <li>Improve the feature of automatic import of events</li> <li>Implement a system for event analytics</li> <li>Implement machine learning capabilities for Big Data Services</li> <li>Implement machine learning capabilities for Search</li> </ul> <p>Project Goals :</p> <ul> <li>Addition of automatic import of events listed on various other event management websites into Open Event so to make it as a one stop resource of events across the web.</li> <li>Implement the features for event analytics which allows the users to see how is the events distributed among various categories or event types in Open Event application. This may also include to analyse the interest of attendees towards every specific event type and event topic.</li> <li>Addition of machine learning capabilities to have big data services include in the Open Event API Server so to manage the data as our application scales.</li> <li>To implement machine learning techniques in events search to provide the user with more specific and interested events result set after searching. </li> <li>Writing tests for all the features improved and introduced.</li> </ul>

<p>Though the basic functionality of Bassa is complete and working, however AngularJS is not much supportive right now so the codebase needs to be shifted to a stable release. ReactJS with Webpack are to be used for creating the new codebase.</p>

Writing unit test cases can be challenging and sometimes not an efficient process. Keploy creates backend API tests with built-in-mocks or stubs by recording your application network calls making your testing process not only faster than unit tests but also incredibly efficient.This project aims to develop a console with keploy which will allow user to have hands on experience with keploy.Capturing the test-cases , replaying the captured test-cases and testing with your favourite library is allowed in the console using keploy. Also Interactive guide will be provided to the user distributed in different parts so that the user can follow through the process easily. Additionaly there will be web-stories so that the user get acquainted with the latest news about Keploy.

<p>Robotics Academy is fully oriented to service Robotics and Computer Vision. It comprises a collection of exercises, including recent service robot applications in real life, with different robots such as autonomous cars, drones, or vacuum cleaners. Industrial Robotics is an open-source collection of resources for JdeRobot and exercises for autonomous robotics manipulation. Last year, they incorporated three exercises based on robot manipulation and navigation. Now, the plan is to extend these exercises to Web Templates. For each exercise, a template performs all the auxiliary tasks such as the graphical interface, connection to the sensors and actuators, timing of the code, etc. This also hosts the student’s code. Using this template, the student focuses on robot intelligence (for instance, perception and control algorithms) without wasting time on auxiliary details with little educational value.</p>

<p>The audience of PySyft largely consists of people who would like to train their model on private data that reside on other devices/locations.</p> <p>Right now one has to manually spin-up Google Cloud Machines, load a PyGrid instance, queue and run training jobs, deposit the results to another long-running instance(Master) and teardown the created instances(Workers).</p> <p>The project aims to implement functionality necessary to automatically spin-up Google cloud machines, load a PyGrid instance, run a training job, and tear down the instance upon completion (depositing the results into another long-running instance). The primary feature will be the ability to run a “hyperparameter sweep”.</p> <p>The sweep function will kill the nodes(Workers) upon completion of training and depositing the results into another long-running instance(Master).</p>

<p>Developer Web Interface for ReactOS will be a single Interface which can address all developer needs from easily watching commits to triggering tests and viewing test results. The interface will be having all details regarding the GitHub repository of ReactOS ranging from commit history to pull requests with the ability of filtering. Moreover, the interface will allow the developers to view the build and test results with details by taking the help of existing ReactOS web tools</p>

This project aims to enhance the GCompris educational suite by introducing a set of intuitive, GUI-based tools tailored for teachers. These tools will allow educators to easily create and manage custom datasets for various activities, improving adaptability and personalization in the learning experience. The activities targeted for dataset creation include: 1.Grammar Analysis 2.Graduated Lines 3.Decimal Numbers 4. Share 5.Fractions Create The core of the solution involves building user-friendly interfaces using QML, allowing teachers to input data without dealing with raw JSON or technical configurations. On the backend, we will enhance and adapt the activity logic using JavaScript to ensure compatibility with both newly created and existing datasets. These tools will be implemented as modular plugins integrated into the GCompris infrastructure. By empowering teachers to contribute customized content directly, the project fosters a more dynamic and inclusive educational environment, catering to diverse learning needs.

Build real-time MQTT 5.0 push notifications and GeoJSON trajectory streams for tracking orbital environmental sensors.

<p>The GNOME.org website needs a redesign (refresh) both in design terms and look-and-feel (UI) terms. This project is about the technical and content-wise evaluation for a possible refresh of the GNOME.org website. This project would include the assessment of the current state of GNOME.org by its content and then a full evaluation of design-wise and content-wise changes.</p>

<p>Security Assertion Markup Language (SAML) is an XML based security token which is used to exchange authentication and authorization data between two entities. It is one of the most widely used open standards to perform brokered authentication and web browser based single-sign-on. "Assertion Query/Request Profile" defines a protocol for requesting dynamic or existing assertions by reference or by querying on the basis of a subject and additional statement-specific criteria. Assertion Query/Request Profile defines five major request/query message types which can be used to request assertions from SAML authority.</p> <ol> <li>AssertionIDRequest</li> <li>SubjectQuery</li> <li>AuthnQuery</li> <li>AttributeQuery</li> <li>AuthzDecisionQuery</li> </ol>

<p>This project is based on the building a web app that can take the user input of the plain-text code or it can take the input as the URL from where the code can be downloaded into the proper directories. It can also allow the user to upload files from the computer.</p> <p>Once the user enters the information, the automating scripts will get the code. Some checks will be applied to check whether the given inputs are correct or not. Further, the scancode library can be used to analyse the user code. Finally, the analysed information will be stored in the database. The data exchange between the scancode and the web app is done using ABCD format as specified by the scancode documentation.</p> <p>The final output will be shown to the user on demand using templates.</p>