In this work, a study of several laser-based 2D Simultaneous Localization and Mapping (SLAM) techniques available in Robot Operating System (ROS) is conducted. All the approaches have been evaluated and compared in 2D simulations and real world experiments. In order to draw conclusions on the performance of the tested techniques, the experimental results were collected under the same conditions and a generalized performance metric based on the k-nearest neighbors concept was applied. Moreover, the CPU load of each technique is examined. This work provides insight on the weaknesses and strengths of each solution. Such analysis is fundamental to decide which solution to adopt according to the properties of the intended final application.

This article presents a survey on cooperative multi-robot patrolling algorithms, which is a recent field of research. Every strategy proposed in the last decade is distinct and is normally based on operational research methods, simple and classic techniques for agent’s coordination or alternative, and usually more complex, coordination mechanisms like market-based approaches or reinforcement-learning. The variety of approaches differs in various aspects such as agent type and their decision-making or the coordination and communication mechanisms. Considering the current work concerning the patrolling problem with teams of robots, it is felt that there is still a great potential to take a step forward in the knowledge of this field, approaching well-known limitations in previous works that should be overcome.