Competition Report RoboCup Rescue Robot and Simulation Leagues H. Levent Akin, Nobuhiro Ito, Adam Jacoff, Alexander Kleiner, Johannes Pellenz, Arnoud Visser n The RoboCup Rescue Robot and Simulation fter the Great Hanshin Earthquake of 1995 in Kobe, the competitions have been held since 2000. The Japanese government decided to promote research relat - experience gained during these competitions has ed to the problems encountered during large-scale urban increased the maturity level of the field, which A disasters. A major outcome of this initiative was the RoboCup allowed deploying robots after real disasters (for example, the Fukushima Daiichi nuclear disas - Rescue competitions. In this article, we introduce the RoboCup ter). This article provides an overview of these Rescue leagues, namely the Rescue Robot League (RRL) and the competitions and highlights the state of the art Rescue Simulation League (RSL) (Tadokoro et al. 2000; Kitano and the lessons learned. and Tadokoro 2001). Disaster mitigation is an important social issue involving large numbers of heterogeneous agents acting in hostile envi - ronments. The associated urban search and rescue (USAR) sce - narios have great potential for inspiring and driving research in multiagent and multirobot systems. Since the circumstances during real USAR missions are extraordinarily challenging (Mur - phy et al. 2008), benchmarks based on them, such as the RoboCup Rescue competitions, are ideal for assessing the capa - bilities of intelligent robots. Robots that can navigate through affected areas after a disaster most likely will also be capable of negotiating the very same environment under normal circum - stances. If robots are able to recognize humans entombed under piles of rubble of collapsed buildings, they will also be able to recognize them within their natural environment. 78 AI MAGAZINE Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved. ISSN 0738-4602 Competition Report The goal of the RoboCup Rescue competitions is simulated body heat, CO 2 levels, and audio signals. to compare the performance of different algo - The harsh terrain is built of different ramps, stairs, rithms for coordinating and controlling teams of and so-called step fields, which consist of a normed either robots or agents performing disaster mitiga - pattern of wooden blocks resembling the structure tion in a simulated yet realistic environment. By of a rubble pile (see figure 1). their nature, the USAR scenarios demand solutions Both remote-controlled and autonomous robots for the coordination of large and distributed teams are allowed in the competitions to foster the of heterogeneous robots. improvement of the mobility of the robots, The competitions are held annually as a part of human-robot interaction, and the development of the RoboCup World Championships. In addition, autonomous agents that are capable of handling regional competitions are held in RoboCup Opens such unstructured environments. To highlight the such as the ones in the United States, Germany, achievements in these categories special awards are the Netherlands, Japan, Iran, Thailand, and China. given for Best-in-Class Autonomy, Best-in-Class The RoboCup Opens are organized by the nation - Mobility, and Best-in-Class Manipulation. al committees, whereas the international competi - Due to the use of standardized test elements, the tions are organized by league organization com - progress of the league over the years can readily be mittees. The competition rules are determined by seen. When the random step fields were intro - the technical committees, whose members are duced in 2005, none of the robots were able to elected annually. cross them in a reliable manner. Today, driving Due to the complexity of the problems through the step fields is the state of the art for the addressed in the competitions, the barrier for the remote-controlled robots. During the same time, entry of new teams is high. For this reason, the fully autonomous robots had to learn handling leagues have recently introduced several measures uneven terrains since their section of the arena was for facilitating software reuse among the teams. no longer flat, but increasingly filled with contin - In the following sections we describe the com - uous or crossed ramps. Such a challenging envi - petitions in RRL and RSL. ronment increases the complexity of path plan - ning and requires an active sensing approach with stabilized distance and victim sensors. Neverthe - Rescue Robot League less, the quality of the generated maps has The Rescue Robot competitions started in 2000 as increased over the years, and all of the competing a part of the AAAI Mobile Robot Competition and teams can now map the whole arena. An example Exhibition, and was later integrated into RoboCup of a very precise map is given in figure 2. This map in 2001. In 2012, approximately 100 teams com - shows both the obstacles in the arena and also the peted in the regional opens; 11 teams from seven victim locations and other landmarks found nations qualified for the world championship in autonomously by the on-board vision system. RoboCup 2012 held in Mexico City. These maps are scored based on the completeness The objective of this league is to promote the of the exploration and accuracy. development of intelligent, highly mobile, dexter - The scientific output of the league over the years ous robots that can improve the safety and effec - include online simultaneous localization and map - tiveness of emergency responders performing haz - ping (SLAM) solutions (Kohlbrecher et al. 2011; Pel - ardous tasks. Annual competitions and subsequent lenz and Paulus 2009; Kleiner and Dornhege 2009) field exercises with emergency responders are used and solutions for efficient exploration strategies to increase awareness about the challenges (Wirth and Pellenz 2007). The performance of these involved in deploying robots for emergency approaches was demonstrated and tested in prac - response applications. They are also used to pro - tice during several RoboCup competitions. The vide objective performance evaluations based on mapping system introduced by Kleiner et al. (2005) DHS-NIST-ASTM international standard test meth - has also been integrated into a commercial robot ods for response robots, introduce best-in-class platform for bomb disposal by the German compa - implementations to emergency responders within ny telerob GmbH and has also been nominated for their own training facilities, and support ASTM the EU technology transfer award for 2011. The International Standards Committee on Homeland robot Quince developed by Japanese universities Security Applications (E54.08.01). and evaluated in the RRL in various iterations was The main task of the competition is to find sim - finally deployed at the Fukushima Daiichi nuclear ulated victims emitting several signs of life in a power plant in the aftermath of the massive earth - maze with different levels of harsh terrain and to quake and tsunami that hit eastern Japan in 2011. indicate the location of the victims and of auto - It was used for inspection missions in highly con - matically detected landmarks on a map generated taminated areas (Nagatani et al. 2011). by the robot online. The signs of life can be the The league has recently established an open visual appearance and movements of the victims, source standard software solution based on Robot SPRING 2013 79 Competition Report Figure 1. Rescue Robot of Team Stabilize from Thailand Inspects a Simulated Victim near a Step Field at RoboCup 2012. Operating System (ROS) that makes the best algo - ware agents and robots that are expected to make rithms broadly reusable, thus enabling the new rational decisions autonomously in a disaster teams to reach quickly the world class performance response scenario. RSL has two major competi - level. 1 tions, namely the Agent and the Virtual Robot competitions. There are described in the subse - Rescue Simulation League quent sections. This league aims to develop realistic simulation Agent Competition environments for benchmarking intelligent soft - The rescue agent competition aims to simulate 80 AI MAGAZINE Competition Report Figure 2. Map Generated by an Autonomous Robot of Team Hector from TU Darmstadt (RoboCup RRL Final 2012). large-scale disasters such as earthquakes and explore new ways of autonomous coordination of heterogeneous rescue teams under adverse condi - tions (Kitano et al. 1999; Tadokoro et al. 2000). 200 1 200 2 200 3 200 4 200 5 2006 This competition was first demonstrated during 7 8 30 34 40 42 RoboCup 2000 and was later launched as an offi - 200 7 200 8 200 9 201 0 201 1 2012 cial competition in 2001. 31 35 22 33 21 22a About 25 university teams participate in the agent competition annually. These teams have their background mainly from AI and robotics and come from different countries such as the United States, Japan, Germany, England, Portugal, Turkey, Iran, and China. Table 1 summarizes the number Table 1. The Numbers of Teams That Participated of teams that participated during the last years. in the Agent Competition during the Last Few Years. The competition is based on a complex simula - a. Includes six teams of the RMas-Bench challenge. SPRING 2013 81 Competition Report Figure 3. A Typical Scenario Involving the Simulation of Fires and Building Collapse on a Model of the City of Kobe in Japan. tion platform representing a city after an earth - missions, coalition formation among agents, and quake (figure 3). Due to the variations among the assignment of agents and coalitions to dynam - potential disaster scenarios, typically rather than a ically changing tasks. In the target domain, these single agent type, strongly diverse teams of agents issue are even more challenging due to the restrict - are required. In the competitions, teams of fire ed communication bandwidth. Moreover, the sim - brigade, police, and ambulance agents try to extin - ulated environment is highly dynamic and only guish fires and rescue victims in the collapsed partially observable by the agents.