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In the future, mobile robots may be able to assist rescue crews in search and rescue missions that take place in the dangerous environments that result from natural or man-made disasters. In 2006, we launched a research project to develop mobile robots that can rapidly collect information in the initial stages of a disaster. One of our important objectives is three-dimensional (3D) mapping, which can be a very useful tool for assisting rescue crews in strategizing rescue missions. To realize this 3D mapping, we identified five issues that we needed to address: (1) autonomous traversal of uneven terrain, (2) development of a system for the continuous acquisition of 3D data of the environment, (3) coverage path planning, (4) centralization of map data obtained by multiple robots, and (5) fusion of map data obtained by multiple robots. We solved each problem through our joint research. Each research institute in our group took charge of solving one of the above issues according to its area of expertise. We integrated these solutions to perform 3D mapping using our tracked vehicle, Kenaf. To validate our integrated autonomous 3D mapping system, we participated in RoboCupRescue 2009 and demonstrated our system using multiple robots on the RoboCupRescue field. In this paper, we introduce our mapping system and report the mapping results obtained at

Mobile robots may be able to aid rescue crews in dangerous environments during search and rescue missions after natural or man-made disasters. In 2006, we began a research project to realize mobile robots that can gather information rapidly at the first stage of a disaster. 3D mapping, which can be an important aid for rescue crews in strategizing rescue missions, is one of our important objectives. Some fundamental elements to enable 3D mapping have been developed. We attended RoboCupRescue 2009 to validate our integrated autonomous 3D mapping system. We demonstrated our mapping system using multiple-robots on the RoboCupRescue field. In this paper, we introduce our mapping system and report the results from the RoboCupRescue competition.

Mobile rescue robots used in search and rescue missions must be able to navigate in unknown environments and map these environments. In such situations, three-dimensional (3D) data obtained by a laser range finder is very useful for supporting teleoperation of robots to locate victims and aid rescue crews in devising rescue strategies. However, when using conventional scanning systems to obtain such 3D data, the operators must wait for a few seconds and halt the operation of the rescue robot. To solve this time-loss-problem, our research group proposed a continuous acquisition system for acquiring 3D environment data for tracked vehicles using the 3D odometry with gyroscope. In locomotion issues, actuated subtracks, attached at the front and the back of the main body to improve stability of the robot, are commonly used to navigate on rough terrains, overcome large obstacles, and maneuver up or down stairs. However, managing actuated subtracks is difficult for the operator because only a small amount of information about the robot pose and environment is available. To assist the operators, our research group developed an autonomous control system based on the terrain data obtained using laser range finders for actuated sub-tracks. In this study, on the basis of the above systems, we developed a teleoperation system for mobile robots that functions effectively under conditions of time-delayed and narrow bandwidth wireless communication. In this paper, we introduce our teleoperation system and report the results of experiments performed to validate the system.

This paper proposes an identity-verification system for attendees of large-scale events using continuous face recognition improved by managing facial directions and eye contact (eyes are open or closed) of the attendees. Identity-verification systems have been required to prevent illegal resale such as ticket scalping. The problem in verifying ticket holders is how to simultaneously verify identities efficiently and prevent individuals from impersonating others at a large-scale event at which tens of thousands of people participate. We previously developed two ticket ID systems for identifying the purchaser and holder of a ticket. These systems use two face-recognition systems, i.e., one-stop face-recognition system with a single camera and non-stop face-recognition system with two cameras. The average face-recognition accuracy was respectively 90 and 91%, and the average time for identity verification from check-in to entry admission was respectively 7 and 2.8 seconds per person. One-stop systems have lower equipment cost than non-stop systems because they require fewer cameras for face recognition. Since both systems were proven effective for preventing illegal resale by verifying attendees of large concerts, they have been used at more than 110 concerts. The problem with both systems is regarding face-recognition accuracy. This can be mitigated by securing clear facial photos because face recognition fails when unclear facial photos are obtained, i.e., when event attendees have their eyes closed, are not looking directly forward, or have their faces covered with hair or items such as facemasks and mufflers. In this paper, we propose a system for securing facial photos of attendees directly facing a camera by leading them to scan their check-in codes on a code-reader placed close to the camera just before executing face recognition. The system also takes two photos of attendees with the single camera after an interval of about 0.5 seconds to obtain facial photos with their eyes open. The system achieved 93% face-recognition accuracy with an average time of 2.7 seconds per person for identity verification when they were used for verifying 8,461 attendees of a concert of a popular music singer. The system made it possible to complete identity verification with higher accuracy than previous systems and with shorter average time than the non-stop system using a single camera, i.e., with low equipment cost. Survey results obtained from the attendees showed that 96.4% felt it provided more equity in ticket purchasing than methods without face recognition, 87.1% felt it provided added convenience in verification, and 95.4% felt it would effectively prevent illegal resale.