From ERL to MBZIRC: Development of An Aerial-Ground Robotic Team for Search and Rescue

Abstract

This chapter describes the efforts of the LARICS team in the 2019 European Robotics League (ERL) Emergency Robots and the 2020 Mohamed Bin Zayed International Robotics Challenge (MBZIRC) robotics competitions. We focus on the implementation of hardware and software modules that enable the deployment of aerial-ground robotic teams in unstructured environments for joint missions. In addition to the overall system specification, we outline the main algorithms for operation in such conditions: autonomous exploration of unknown environments and detection of objects of interest. Analysis of the results shows the success of the developed system in the competition arena of two of the largest outdoor robotics challenges. Throughout the chapter, we highlight the evolution of the robotic system based on the experience gained in the ERL competition. We conclude the chapter with key findings and additional improvement ideas to advance the state of the art in search and rescue applications of heterogeneous robotic teams.

UAV Autonomous Indoor Exploration and Mapping for SAR Missions: Reflections from the ICUAS 2022 Competition

“…Existing works in autonomous UAV exploration missions focus on a target-oriented approach to recognize objects of interest in an unknown environment and reach them efficiently [7], [8]. To emulate real-life SAR missions and allow comparative assessment of competing solutions under challenging conditions, several events were organized in the past [9], including the 2020 Mohamed Bin Zayed International Robotics Challenge 1 (MBZIRC) wherein multiple challenges were held, especially the challenge 3 targeted an urban firefighting scenario for cooperated aerial and ground vehicles to navigate, detect, approach, and extinguish multiple simulated fires around and inside a building [10]. Another was the DARPA Subterranean (SubT) Challenge 2 based on extreme conditions in underground environments: humanmade tunnels, the urban underground, and natural caves, to perform challenging autonomous exploration missions [11].…”

Advanced Power Converters and Learning in Diverse Robotic Innovation: A Review

“…Search-and-Rescue Missions: The integration plays a pivotal role in enhancing robotic capabilities for search-and-rescue operations. By efficiently managing power resources, robots can operate in disaster-stricken areas for extended durations, maximizing their chances of locating and aiding survivors [219,220]. Learning approaches enable these robots to adapt their search patterns based on evolving conditions and past experiences, significantly increasing their effectiveness in locating and assisting individuals in distress [221,222].…”