What are the most effective LiDAR robotics training programs?

Identifying effective LiDAR robotics training programs depends on specific goals and proficiency levels. Platforms like Coursera, Udacity, and edX offer various courses covering LiDAR technology, sensor fusion, and robotics applications. Online tutorials and documentation from LiDAR manufacturers, such as Velodyne and Livox, provide practical insights. Open-source robotics communities like ROS offer extensive resources for LiDAR integration. Additionally, workshops and conferences by organizations like IEEE and RoboBusiness often feature LiDAR-related sessions. Tailor your selection based on your learning style, skill level, and specific LiDAR applications.

I would suggest courses from Anis Koubaa. They cover the details and help in making the map creation and much more. This is one of the best courses for ROS I have gone through.

Coursera's Self-Driving Car Specialization, developed by the University of Toronto and the University of Waterloo, immerses learners in autonomous vehicles' intricate world. It covers pivotal domains: computer vision, deep learning, sensor fusion, localization, and control systems. Sub-courses like "Introduction to Self-Driving Cars," "State Estimation and Localization," "Visual Perception," and "Motion Planning" delve into these areas. Hands-on projects with real-world data and simulations bridge theory with practice, empowering students to gain practical insights. This prepares them for challenges in this evolving field, fostering skills crucial for driving innovations in autonomous vehicles.

Go through courses by Constructsim. It would help you do the simulation online and control a teleoperated robot which is in their environment.

Making open-source contributions to packages like PCL, Open3d and many others can help you to learn a lot about this topic. There are many open-source Lidar databases that you can use to build projects which will give you hands-on experience working on Lidar + Robotics.

Udacity's Self-Driving Car Engineer Nanodegree prepares individuals for careers in autonomous vehicle tech. In partnership with industry leaders like Mercedes-Benz, NVIDIA, and BMW, it covers vital concepts: computer vision, sensor fusion, localization, path planning, and control. Sub-courses delve into "Computer Vision," "Deep Learning," "Sensor Fusion," "Localization," "Path Planning," and "Controls." Hands-on projects involve implementing algorithms on real vehicles or simulators, granting crucial practical experience for success in this dynamic field. This Nanodegree empowers learners to design, develop, and deploy self-driving car systems, meeting the industry's rapid evolution.