Isbn: 9788409871711 - autonomous drones ii: robotic, computer vision, ai (8 resultados)

Paperback or Softback. Condición: New. Autonomous Drones II: Robotics, Computer Vision, AI. Book.

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: new. Paperback. You have mastered the fundamentals (Volume 1). Now it is time to take it to the next level: intelligent autonomy.This book teaches you how to integrate robotics, computer vision, and artificial intelligence into real drones. Perfect for engineers looking to specialise in autonomous perception.Chapter 1 - ROS2 and Robotic Architecture- The de facto operating system in professional robotics.- Nodes, topics, messages - decentralised architecture.- Ardupilot + ROS2 integration (MAVLink bridge).- Nav2: 3D autonomous navigation stack.- Simulation with Gazebo + SITL.Chapter 2 - Computer Vision and Object Detection- OpenCV: real-time image processing.- YOLOv8: ultra-fast detection (45 FPS on GPU).- Classical methods vs. Deep Learning.- Integration with ROS2 (image publishers/subscribers).- Real-world use cases: detection of people, vehicles, points of interest.Chapter 3 - AI in Drones- Edge Computing: processing on the drone, not in the cloud.- Jetson line (Nano Orin): selection based on latency and budget.- Latency - TensorRT: 2-3x acceleration of NN models.- Complete architecture: Jetson + ROS2 + Ardupilot + vision.Key Features: - 246 pages of applied content.- Ready-to-use Python/C++ code.- 20+ graphs and flow diagrams.- Compatible with hardware: Jetson Nano, Orin NX, RTX.- Preparation for research/commercial drones.Prerequisites: - Familiarity with Python (Appendix A2).- Drone concepts (Volume 1).- Ubuntu 22.04 recommended.Who is it for?- Engineers specialising in robotic autonomy.- Researchers in computer vision.- AI drone startups.- Makers who want "intelligent" drones.From object detection to autonomous decision-making, you will learn the complete stack of intelligent drones.All examples, practices, exercises and exams are solved and available on GitHub: Take your drones to the next level with ROS2, computer vision (YOLOv8, OpenCV) and embedded AI on Jetson. Complete stack for intelligent autonomy. Python/C++ code and architecture diagrams. Source code available on GitHub. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. You have mastered the fundamentals (Volume 1). Now it is time to take it to the next level: intelligent autonomy.This book teaches you how to integrate robotics, computer vision, and artificial intelligence into real drones. Perfect for engineers looking to specialise in autonomous perception.Chapter 1 - ROS2 and Robotic Architecture- The de facto operating system in professional robotics.- Nodes, topics, messages - decentralised architecture.- Ardupilot + ROS2 integration (MAVLink bridge).- Nav2: 3D autonomous navigation stack.- Simulation with Gazebo + SITL.Chapter 2 - Computer Vision and Object Detection- OpenCV: real-time image processing.- YOLOv8: ultra-fast detection (45 FPS on GPU).- Classical methods vs. Deep Learning.- Integration with ROS2 (image publishers/subscribers).- Real-world use cases: detection of people, vehicles, points of interest.Chapter 3 - AI in Drones- Edge Computing: processing on the drone, not in the cloud.- Jetson line (Nano Orin): selection based on latency and budget.- Latency - TensorRT: 2-3x acceleration of NN models.- Complete architecture: Jetson + ROS2 + Ardupilot + vision.Key Features: - 246 pages of applied content.- Ready-to-use Python/C++ code.- 20+ graphs and flow diagrams.- Compatible with hardware: Jetson Nano, Orin NX, RTX.- Preparation for research/commercial drones.Prerequisites: - Familiarity with Python (Appendix A2).- Drone concepts (Volume 1).- Ubuntu 22.04 recommended.Who is it for?- Engineers specialising in robotic autonomy.- Researchers in computer vision.- AI drone startups.- Makers who want "intelligent" drones.From object detection to autonomous decision-making, you will learn the complete stack of intelligent drones.All examples, practices, exercises and exams are solved and available on GitHub: Take your drones to the next level with ROS2, computer vision (YOLOv8, OpenCV) and embedded AI on Jetson. Complete stack for intelligent autonomy. Python/C++ code and architecture diagrams. Source code available on GitHub. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condición: new. Paperback. You have mastered the fundamentals (Volume 1). Now it is time to take it to the next level: intelligent autonomy.This book teaches you how to integrate robotics, computer vision, and artificial intelligence into real drones. Perfect for engineers looking to specialise in autonomous perception.Chapter 1 - ROS2 and Robotic Architecture- The de facto operating system in professional robotics.- Nodes, topics, messages - decentralised architecture.- Ardupilot + ROS2 integration (MAVLink bridge).- Nav2: 3D autonomous navigation stack.- Simulation with Gazebo + SITL.Chapter 2 - Computer Vision and Object Detection- OpenCV: real-time image processing.- YOLOv8: ultra-fast detection (45 FPS on GPU).- Classical methods vs. Deep Learning.- Integration with ROS2 (image publishers/subscribers).- Real-world use cases: detection of people, vehicles, points of interest.Chapter 3 - AI in Drones- Edge Computing: processing on the drone, not in the cloud.- Jetson line (Nano Orin): selection based on latency and budget.- Latency - TensorRT: 2-3x acceleration of NN models.- Complete architecture: Jetson + ROS2 + Ardupilot + vision.Key Features: - 246 pages of applied content.- Ready-to-use Python/C++ code.- 20+ graphs and flow diagrams.- Compatible with hardware: Jetson Nano, Orin NX, RTX.- Preparation for research/commercial drones.Prerequisites: - Familiarity with Python (Appendix A2).- Drone concepts (Volume 1).- Ubuntu 22.04 recommended.Who is it for?- Engineers specialising in robotic autonomy.- Researchers in computer vision.- AI drone startups.- Makers who want "intelligent" drones.From object detection to autonomous decision-making, you will learn the complete stack of intelligent drones.All examples, practices, exercises and exams are solved and available on GitHub: Take your drones to the next level with ROS2, computer vision (YOLOv8, OpenCV) and embedded AI on Jetson. Complete stack for intelligent autonomy. Python/C++ code and architecture diagrams. Source code available on GitHub. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

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