Computer Engineering / Hardware

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https://hdl.handle.net/20.500.11888/10126

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Now showing 1 - 5 of 895
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    The Prime Robot
    (2025) Younis Masri; Yanal Oudeh
    The Prime Robot is a smart robotic assistant designed to demonstrate a complete, end-to- end human–robot interaction (HRI) stack that is safe, intuitive, and adaptable. The system integrates perception, decision, and actuation in a modular pipeline: it interprets user intent through multimodal inputs—hand gestures, Bluetooth commands, and voice— arbitrates behavior with a safety-first controller, and executes smooth, coordinated arm actions. A signature capability is Follow Mode: with a single activation gesture, the robot enters a hands-free mode that autonomously continues the assigned task while continuously monitoring proximity; it pauses when a safety threshold is reached and automatically resumes once conditions are clear. An explicit stop gesture exits Follow instantly, and safety interlocks remain active across all modes. Beyond Follow, the platform supports direct driving (forward/turn/reverse/stop), a configurable speed interface, and a demonstration arm sequence for simple pick-and-place routines. A lightweight mobile interface can be used to switch modes, issue commands, and review status remotely. The architecture is deliberately hardware-agnostic and built around clean software boundaries, enabling replication in educational labs and easy substitution of sensors or compute without redesigning the control logic. The Prime Robot is designed as a practical assistant: it analyzes the user’s hand gestures in real time and performs the corresponding actions—moving forward, turning, stopping, triggering simple arm routines, or entering/exiting Follow mode. By prioritizing clear intent recognition and conservative proximity safeguards, it reduces operator effort and ambiguity in shared spaces while delivering responsive, predictable behavior for instructional and service settings. Future work will expand the gesture vocabulary, refine the decision policy, add soft start/stop and richer status feedback, and conduct user studies to evaluate accuracy, comfort, and trust.
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    Seseam Circle
    (2025) Israa Majed Al-Salman; Aya Wael Ahmad
    This project presents the design and installation of a semi-automatic production line for Sesame Circle, a traditional sesame biscuit. The system improves efficiency, hygiene, and consistency by automating key steps such as dough cutting, shaping, flavoring, baking, and packaging. The goal is to deliver a cost-effective and scalable solution for small bakeries while preserving the authentic taste and tradition of the product.
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    Wall-coating Robot
    (2026) Rand Johari; Asmaa Lahlabat
    This project presents the design and development of a wall-painting system that aims to improve efficiency, consistency, and safety in wall-coating tasks. The robot automates key parts of the process by using sensors and control logic to detect paintable surfaces, plan coverage paths, and apply paint with minimal human intervention. The work focuses on achieving reliable and repeatable motion, reducing manual effort and rework, and maintaining good coating quality. The system is tested and tuned to evaluate coverage uniformity, operational stability, and ease of use. Although commercial robotic painting solutions exist, this project represents a novel and practical student implementation in our department and serves as a step toward smarter and more automated painting workflows.
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    MazeSolver
    (2026) Abdalrahman Masri; Motaz Qarmash
    This project entails designing and constructing an autonomous robot, MazeSolver, to solve mazes using the Flood Fill algorithm. Motivated by the rising significance of autonomous navigation in disaster response, smart manufacturing, and logistics automation, the objective is to demonstrate real-time decision-making through sensor feedback and algorithmic path planning [3, 4, 5]. The robot employs three IR sensors and a VL53L0X Time-of-Flight LiDAR for environmental mapping, dynamically updating its internal map upon detecting obstacles [15, 16]. Utilizing the Flood Fill algorithm, it adapts its path in real-time, striving to select the shortest route despite an initially unknown maze layout. Development involved hardware design with an ESP32 microcontroller, sensor calibration, programming in Arduino C++, and testing in a physical 7x6 maze, with movement controlled by two DC motors with encoders via an L298N driver and orientation maintained by an MPU6050 gyroscope [9, 12]. Communi- cation is facilitated by a remote unit with a second ESP32 using the ESP-NOW protocol [1]. MazeSolver distinguishes itself from predecessors like Micromouse through its real-time wall detection and dynamic replanning, enhancing adaptability for applications such as warehouse robots, search-and-rescue units, and agricultural machines in unpredictable environments.
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    Hot Drinks machine
    (2025) Malik Taiseer Ali; Shaheen Ali Abbas
    The main idea of our project is to build a fully-automated Hot Drinks Machine to be working instead of depending on human resources in the making hot drinks such as coffee, cappuccino, and Nescafé, the machine we built is controlled by a main controller built in the machine and a mobile application; it also includes features that were not included in some coffee machines. We tried our best, and we used sensors and electronic pieces to guarantee the efficiency and accuracy of the project. Generally, the main features like automated cup dispensing mechanism, Dedicated powder containers corresponding to different beverage types dispense precise quantities of powder Each container is equipped with an ultrasonic sensor to monitor powder levels and generate refill alerts when necessary, A heated water tank maintains the required water temperature through continuous monitoring using a temperature sensor while a pump regulates the controlled delivery of hot water into the cup, and a mechanical stirring mechanism ensures proper mixing to achieve uniform beverage quality. The integration of sensors, actuators, and embedded control logic results in an efficient, consistent, and user-friendly automated solution, illustrating the effectiveness of automation technologies in modern beverage production lines.