Navigation Strategies for autonomous robotic systems

Expected skills : 32 (322/323), 34 (342/343), 112 (1121/1122)

In this course, you will learn to implement perception, localisation, navigation and communication techniques in order to design an autonomous robotic system. This one needs to interact with its environment as well as with the other fixed or mobile entities. Moreover, the training will focus on the implementation of a vision based control, navigation control algorithms (e.g. SLAM) and communication architectures (ROS, MQTT). Application cases will be presented by robotics companies to illustrate the use of these techniques on use cases. An awareness of industrialization and the constraints that it induces in the design of robotic systems will also be addressed.

At the end of this course, the student should be able to:
Design and develop an autonomous robotic system by choosing the appropriate navigation algorithms, taking into account the industrialization constraints
Know how to design the robot's communication architecture and software
Know how to implement a vision referenced control algorithm on a robot
Know how to implement a localisation and navigation algorithm (e.g. SLAM) on a robot using ROS

Some of the pedagogical approaches in this module allow you to work on transversal skills such as project management, report writing and oral communication.