AI Ardupilot Drone Interceptor

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@Ravan011patel

As a seasoned Robotics and Software Engineer, with a specialization in Computer Vision and a strong background in handling AI integration tasks, I believe I am ideally suited to meet and exceed your interceptor drone project needs. Having worked extensively with the Ardupilot flight stack as well as Python, OpenCV, TensorFlow among others, my team and I are fully capable of integrating the AI pipeline effectively while delivering real-time object recognition results to the flight controller with exceptional turnaround time - 20 Hz or better as required. Moreover, my portfolio features successful implementations of autonomous systems using Ardupilot, showcasing my comprehensive understanding of its GUIDED modes and mavlink commands. This expertise is only primed to enhance your project as my dedication to clean execution and swift deployment has always yielded smooth SITL tests and flawless compilations, which will be paramount for this project. Lastly, I'd like to emphasize that my approach combines engineering scalability with startup speed execution - a perfect harmony for your requirements. This means not only meeting your core necessities proficiently but also ensuring long-term support through comprehensive documentation, setup guides, as well as vivid demonstration videos for allour deliverables. Let's join forces for a venture that doesn't just meet expectations but also sets new industry standards.

@SaadMubee

Hi there, I see you're working on an innovative proof-of-concept for a drone interceptor that leverages the Ardupilot flight stack alongside an onboard AI module. Your goal to have the aircraft autonomously identify and track other drones is both ambitious and exciting, and I believe I can assist you in bringing this concept to fruition. To address your requirements, I propose a tailored approach focused on integrating a robust AI pipeline with your Ardupilot setup. I can deliver well-documented code for the vision stack using Python with TensorFlow, ensuring reliable object recognition and seamless communication with the flight controller through mavlink commands. I will also create a comprehensive setup guide that outlines all necessary hardware connections, firmware parameters, and video pipeline configurations. Furthermore, I’ll conduct extensive testing to ensure the system successfully detects drone-class objects and maintains them in frame for the specified duration. What specific timelines do you have in mind for the testing phases of this project? https://www.freelancer.com/u/saadmubee Best regards, Saad Mubee.

@mudassirs52

✔ I deliver 100% reliable integration — AI vision + Ardupilot guidance working as one unified system. ✔ Workflow Diagram Live Video Feed ⟶⟶ AI Detection & Classification ⟶⟶ Target Coordinates (20 Hz) ⟶⟶ Mavlink/Lua Guidance Layer ⟶⟶ Ardupilot GUIDED Mode Tracking ⟶⟶ Stable Intercept Pattern Key Highlights ✔ End-to-end AI vision stack — optimised Python/C++ pipeline using TensorFlow, YOLOv8/YOLO-NAS, or TensorRT for real-time throughput. ✔ Ardupilot autonomous tracking — custom MAVLink or Lua scripts that translate bounding boxes into heading, pitch, and velocity adjustments. ✔ 20 Hz real-time coordinate feed — stable, low-latency target updates with buffering and fail-safe logic. ✔ Configurable standoff distance — adjustable in a param file so you can tune proximity behaviour without code edits. ✔ SITL + real-quad compatibility — verified in simulation first, then deployable to your actual aircraft with minimal changes. ✔ Modular codebase — clean separation between vision, communication, and guidance for easy upgrades later. ✔ Documented from wiring to firmware — hardware diagram, GStreamer or RTSP pipeline setup, Ardupilot params, and test steps. Best Regards, Asad AI Vision Engineer | Ardupilot & Robotics Integration Specialist | Python/C++ | Real-Time Systems

@SU790609

Hello there! I've carefully reviewed your project requirements and am excited to offer my services. With over 19 years of experience in full-stack and mobile programming and architecture, I believe I'm an ideal match for your needs. My expertise spans a wide range of technologies including Python, Java, Spring Boot, Node.js, Django, React, Angular, and Golang, and I’ve also designed and integrated AI-driven solutions using tools like ChatGPT and Google Gemini to streamline workflows and enhance productivity. My background in domains such as Manufacturing, Automotive, GIS, IoT, and Compliance, combined with experience working with industry leaders like FCA, Cummins, Flex, and Tripwire, equips me to deliver high-quality, timely, and business-focused results across diverse projects. What sets me apart is not just my technical skills, but also my commitment to deeply understanding your goals and choosing the most effective, scalable solutions for your specific use case. I am passionate about leveraging my experience to help you build robust, future-ready systems that are easy to maintain and evolve. If you find my experience aligns with your project requirements, I would be delighted to further discuss how I can contribute to your success. Please feel free to reach out at a time convenient for you—I am keen to explore this opportunity to collaborate and drive your project forward as per your needs. Warm regards, Sujit