Abstract:The ARS 548 RDI Radar is a premium model of the fifth generation of 77 GHz long range radar sensors with new RF antenna arrays, which offer digital beam forming. This radar measures independently the distance, speed and angle of objects without any reflectors in one measurement cycle based on Pulse Compression with New Frequency Modulation [1]. Unfortunately, there were not any drivers available for Linux systems to make the user able to analyze the data acquired from this sensor to the best of our knowledge. In this paper, we present a driver that is able to interpret the data from the ARS 548 RDI sensor and produce data in Robot Operation System version 2 (ROS2). Thus, this data can be stored, represented and analyzed by using the powerful tools offered by ROS2. Besides, our driver offers advanced object features provided by the sensor, such as relative estimated velocity and acceleration of each object, its orientation and angular velocity. We focus on the configuration of the sensor and the use of our driver and advanced filtering and representation tools, offering a video tutorial for these purposes. Finally, a dataset acquired with this sensor and an Ouster OS1-32 LiDAR sensor for baseline purposes is available, so that the user can check the correctness of our driver.
Abstract:The paper presents a presents a framework for fire extinguishing in an urban scenario by a team of aerial and ground robots. The system was developed for the Challenge 3 of the 2020 Mohamed Bin Zayed International Robotics Challenge (MBZIRC). The challenge required to autonomously detect, locate and extinguish fires in different floors of a building, as well as in the surroundings. The multi-robot system developed consists of a heterogeneous robot team of up to three Unmanned Aerial Vehicles (UAV) and one Unmanned Ground Vehicle (UGV). The paper describes the main hardware and software components for UAV and UGV platforms. It also presents the main algorithmic components of the system: a 3D LIDAR-based mapping and localization module able to work in GPS-denied scenarios; a global planner and a fast local re-planning system for robot navigation; infrared-based perception and robot actuation control for fire extinguishing; and a mission executive and coordination module based on Behavior Trees. The paper finally describes the results obtained during competition, where the system worked fully autonomously and scored in all the trials performed. The system contributed to the third place achieved by the Skyeye team in the Grand Challenge of MBZIRC 2020.