Optimal Task Assignment and Collision Avoidance for Mobile Robots

This report serves as a general overview of the semester project conducted in the SYCAMORE lab during the Spring 2022 semester. It focuses on multi- agent optimal task assignment methods, which have been implemented on state of the art simulation methods using frameworks such as ROS2 and Gazebo. Different assignment problems, such as the Linear Sum Assignment Problem and the Lexicographic Bottleneck Assignment Problem, are imple- mented in this simulation platform. This enables a comparative assessment of the respective properties that can be derived from them, such as dynamic con- sistency and collision-avoidance. Visualisation methods are also generated as outputs to enable user-friendliness for the study of the various assignments.