Hands-On ROS for Robotics Programming

Summary

This chapter provided a quick introduction to ML in robotics. We expect you to have acquired insight into what ML and deep learning are, qualitatively understood how a neural network processes images to recognize objects, and can operationally implement the algorithm in a simulated and/or physical robot.

ML is a very wide field and you should not expect nor really need to get an expert in the field. What you need to assimilate is the knowledge to integrate deep learning capabilities in your robots.

As you have seen in the practical case, we have used a pretrained model that covers common objects. Then, we have simply used this model and have not needed additional training. There are plenty of trained models on the web shared by data ...