Summary
This chapter focuses on integrating computer vision algorithms with robotics. This integration allows robots to perceive their environment, detect objects, and better understand the world they operate in. However, computer vision is a complex field. Efficiently processing images and 3D data can be challenging. To simplify these computations, the robotics community often uses off-the-shelf libraries like OpenCV and PCL. In this chapter, we utilized these libraries, interfacing them with sensors such as a standard USB webcam and a RealSense depth sensor. We also explored ways to accelerate these tasks, first through GPU-based calculations and later by applying machine learning techniques for object detection and classification, using NVIDIA’s ROS ISAAC framework and the YOLOv8 library.
This chapter concludes the second part of the book. Moving forward, we will build on what we’ve learned to explore advanced tools and applications in robotics. The next chapter...
