Synopsis
Build robots that can see, understand, map, and navigate the world around them.
This practical, project-driven guide takes you from the foundations of robotic vision to the development of complete autonomous navigation systems using ROS2 and OpenCV. Rather than focusing on isolated concepts, you'll build a scalable perception pipeline that evolves chapter by chapter into a fully integrated robotics platform capable of real-time sensing, tracking, mapping, localization, and intelligent decision-making.
Starting with camera integration, image processing, and ROS2 communication, you'll learn how to create efficient perception systems, optimize performance, and design robust software architectures for real-world deployment. As the journey progresses, you'll implement object detection, feature tracking, stereo and depth perception, visual odometry, sensor fusion, SLAM, path planning, obstacle avoidance, and autonomous navigation while applying industry-standard engineering practices throughout.
Inside, you'll learn how to:
• Build high-performance robotic vision pipelines with ROS2 and OpenCV
• Process, analyze, and optimize real-time image streams
• Implement object detection, tracking, and scene understanding systems
• Develop stereo vision and depth-estimation solutions
• Perform visual odometry and sensor fusion for improved localization
• Construct SLAM systems for mapping and navigation
• Design autonomous path-planning and obstacle-avoidance frameworks
• Optimize robotics applications for edge devices and embedded platforms
• Debug, profile, and deploy production-ready robotic software architectures
Whether you're a student, robotics enthusiast, researcher, or professional engineer, this book provides the practical skills and technical foundation needed to design intelligent robots capable of perceiving their environment and navigating autonomously in complex, dynamic environments.
By the end of the book, you'll have the knowledge and hands-on experience to build advanced robotic perception and navigation systems that bridge the gap between theory and real-world autonomous robotics.
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