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The authors are researching about Three dimensional mapping using mobile robot and 3-D laser scanner. We developed 3-D laser scanner which can measure whole 3-D shape with a combination of 2-D laser scanner and Pan-Tilt base. However, measuring surrounding areas using the scanner on mobile robot, there are some areas where can't measure whole 3-D shape caused by overview camera and wireless LAN's aerial mounted on a robot. In this paper, 3-D laser scanner can measure uniform and whole 3-D shape, which tilts constant value around pitch axis and then rotates one revolution around yaw axis. We propose measuring method that decrease effects of hidden objects by making offset between 2-D laser scan plane and pitch axis.

This paper proposes robust localization method using a free-space observation model with a 3D map for a particle filter. The free-space observation model judges whether the free space of a laser beam of a sensor is appropriate. The observation model realizes highly robust localization in outdoor environments with many unknown obstacles. This paper describes the free-space observation model and the increase in the calculation speed of the observation model. The proposed localization method achieves 1-km localization in outdoor environments with many unknown objects.

This thesis describes a new method that in real time predicts fall and collision in order to support remote control of a tracked vehicle with sub-tracks. A tracked vehicle has high ability of getting over rough terrain. However, it is difficult for an operator at a remote place to control the vehicle's moving direction and speed. Hence, we propose a new path evaluation system based on the measurement of environmental shapes around the vehicle. In this system, the candidate paths are generated by operator inputs and terrain information. For evaluating the traversability of the path, we estimate the pose of the robot on the path and contact points with the ground. Then, the combination of translational and rotational velocity is chosen.

Rapid information gathering during the initial stage of investigation is an important process in case of disasters. However this task could be very risky for human rescue crews, when the infrastructure of the building has been compromised or the environment contaminated by nuclear, biological, or chemical weapons. To be able to develop robots that can go inside the site instead of humans, several area of robotics need to be addressed and integrated inside a common robotic platform. In this paper, we described the modular interoperable and extensive hardware and software architecture of Quince, a high degree of mobility crawler type rescue robot having four independent sub-crawlers. To facilitate Quince's navigability, we developed and integrated a semi-autonomous control algorithm that helps the remote operator driving Quince while the flippers are autonomously adjusting to the environment. The robot is then able to overcome obstacles and steps without a special training of the operator. We present here the software integration and the control strategy of the flippers using the embedded basic version of Quince.

The authors aim at recognition of multiple objects by using robot vision and its manipulation. In the case where multiple objects are arranged in a shelf, front objects may conceal some objects behind them. A robot can recognize these objects if it can recognize the front objects using prior knowledge and remove them with its arm. However, it sometimes fails to recognize the objects because of the lack of good features, a bad lighting condition etc. Here, we proposed a new method of the multi-object recognition using the manipulation. Recognized objects are removed using pickup motion. Unrecognized objects are pushed for changing the angle when the robot cannot recognize them. We show the experimental results of our proposed method. From the results, we can confirm that the manipulation is useful for improving the multi-object recognition.

Gyro-based odometry is an easy-to-use localization method for tracked vehicles because it uses only internal sensors. However, on account of track-terrain slippage and transformation caused by changes in sub-track angles, gyro-based odometry for tracked vehicles with sub-tracks experiences difficulties in estimating the exact location of the vehicles. In order to solve this problem, we propose an estimation method with 6 degrees of freedom (DOF) for determining the position and pose of the tracked vehicles using terrain information. (In this study, position refers to the robot's position and pose.) In the proposed method, position are estimated using a particle filter. The subsequent position of each particle are predicted using a motion model that separately considers each contact point of the vehicle with the ground. In addition, each particle is analyzed using terrain and gravity information. Experimental results demonstrate the effectiveness of this method.

2-Alkoxy-4-amino-N-[(4-benzyl-2-morpholinyl)methyl]-5-chlorobenzamides had been identified as the interesting members of a series of selective and potent gastroprokinetic agents. A new series of 2-amino- and 2-(substituted amino)-N-[(4-benzyl-2-morpholinyl)methyl]benzamides (13-35) has been synthesized and these compounds were examined to determine whether they have advantages over the 2-morpholinyl benzamides 1 with a 2-alkoxy group.The gastroprokinetic activity was generally reduced, but several compounds showed relatively potent activity, comparable to that of the standard agent, metoclopramide. N-[(4-Benzyl-2-morpholinyl)methyl]-4-chloro-2-[(4-chlorobenzoyl)amino]benzamide (32) showed the most potent activity in this series.

This paper provides valuable information about 3-D map construction using a tracked vehicle at Disaster City. Disaster City is a training facility for the Federal Emergency Management Agency (FEMA) in the United States. FEMA staff used our rescue robot Kenaf to conduct simulated emergency testing. Kenaf is a tele-operated tracked vehicle that has high mobility suitable for use in outside terrains and inside buildings. We equipped Kenaf with a 3-D laser scanner that can measure dense and wide angle 3-D shapes. We collected about 50 3-D mapping data sets during the tests. A part of these data sets can be accessed at our website. In this paper, we explain the Kenaf's tele-operation system, the 3-D mapping system, and the comments about the usability of the 3-D mapping from FEMA staff. In addition, we discuss about the limit of our mapping method on the basis of the trials at Disaster City. This information will be helpful for researchers in the robotics to improve their method of 3-D map construction and their tracked vehicles.

Rapid information gathering during the initial stage of investigation is an important process in case of disasters. However this task could be very risky, or even impossible for human rescue crews, when the environment has contaminated by nuclear, biological, or chemical weapons. We developed the information gathering system using multiple mobile robots teleoperated from the safe place, to be deployed in such situation. In this paper, we described functions of the system and report the field experiment conducted in a real underground mall to validate its usability, limitation, and requirements for future developments.

The authors attempted to create a 3-D map of an underground mall and subway station using a tracked vehicle. This paper is a field report of the 3-D mapping of the Sendai subway station by the tracked vehicle in Dec. 2007. From the ticket barriers to the platform, the Sendai subway station consists of three floors. For the 3-D mapping, we developed a tracked vehicle named “Kenaf”, a small and light-weight 3-D laser scanner called TK scanner, and a robust 3-D scan matching method. Kenaf can pass through ticket barriers and climb up and down stairs, while TK scanner has a wide view angle and can measure dense 3-D shapes. During the experiment, the robot stopped at different points and collected 3-D scan data. The 3-D shapes were recorded by the TK scanner as point clouds. These 3-D point clouds were integrated into a map on the basis of odometry data on-line. The constructed map was not correct because of the lack of robot position z and the odometry error. The 3-D map was constructed by matching these 3-D point clouds off-line. To increase the robustness of the matching, we used the iterative closest point (ICP) matching method with a gravity constraint.

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.

Rollover avoidance for tracked vehicles with sub-tracks is a difficult, but necessary task. In this study, rollover avoidance, specifically in the direction of the roll, is performed using a normalized energy stability margin which requires the estimation of a robot's tumble axis. However, a precise estimation of the tumble axis is very difficult because it requires accurate distributed contact information about the robot's main and sub-tracks. In this study, the authors propose a method for rollover avoidance that does not require such accurate contact information. The validity of the stability margin is shown, and it is used to realize rollover avoidance in the direction of the roll.

The authors aim at the development of a 3D laser scanner that can measure uniform and dense 3D shape of static objects in dynamic environment. The 3D scanner was composed of a 2D Laser Range Finder (LRF) and Pan-Tilt base. 3D shape is measured by rotating 2D LRF that is tilted around the two axes. The laser point trajectory shows cross scan. Use of cross scan achieved the wide view angular and the uniform 3D scan. The proposed 3D scanner can adjust the measurement area and the density of 3D point clouds by changing the angle and angular velocity of the pan-tilt mechanism. The 3D scanner can decrease 3D measurement time. In addition, this 3D scanner measures same area twice during one 3D scan. Comparing these two measurement distances, the moving object can be detected.

In this chapter, we summarize the findings and knowhow in the individual developments of rescue robots and attempt to establish design guidelines for the human interface for rescue robots. The guidelines for image display were established on the basis of some case studies in the DDT project and RoboCupRescue. Since the established guidelines are general and independent of the purpose of a robot, we decided to build a standardized image display prototype. After introducing some implementation examples based on our guidelines, the standardized image display prototype is presented. The established guidelines would be useful for the future development of rescue robots. Further, the prototype image display is a good example of a standardized interface testbed.

Intelligent rescue systems with advanced information and robot technology have been expected to mitigate disaster damage, particularly in Japan after the 1995 Hanshin-Awaji Earthquake. It is important that the robots developed for search and rescue tasks can actually work at a real disaster site. Several robots were used for the search and detection operation in the collapsed World Trade Center building in September 2001. In 2002, the DDT Project (Special Project for Earthquake Disaster Mitigation in Urban Areas, III-4 Development of Advanced Robots and Information Systems for Disaster Response) was launched by MEXT (Ministry of Education, Culture, Sports, Science and Technology, Japan). It was a 5-year project for 2002–2007. It aimed at developing necessary technologies for mitigating the damage caused by large-scale earthquakes of the scale of the Great Hanshin-Awaji Earthquake, occurring in densely populated areas in big city regions such as the Tokyo metropolitan area and Keihanshin area. In this paper, we introduce the activities of the mission unit for the information collection by on-rubble mobile platforms.

We aim at developing an autonomous rollover protection system for rescue robots. In this study, we propose a method for autonomous rollover protection for tracked mobile robots using distributed touch sensors. We developed touch sensors for tracked robots, and we have also installed them into our developed tracked robot having four flipper arms. We have also explained the system construction and evaluation. The energy stability margins are used for rollover protection. The autonomous rollover protection system was implemented in our robot. Our system can enable the robot to avoid rollovers during a step climb without the manual control of the flipper arms.

In the case of simulators of mobile robots, it is necessary to clarify the similarity between actual and simulated robots in order to improve the efficiency and transparency of simulators as research tools. Because of its real-time performance, USAR-Sim [1] has been popularly used in studies involving human-robot interactions. However, since USARSim uses approximations and abbreviations in its physical computations, there are some doubts over its computational accuracy. The objective of this study is to compare the actual and simulated robots in order to investigate whether the simulated environments can be used as a training tool. The authors modeled two types of response robots -IRS Soryu [2] and Kenaf [3]- and compared the abilities of the simulated robots and the actual robots in navigating obstacles such as steps and trenches. The dimensions such as heights, widths and lengths and total mass of the real robots were accurately modeled in the simulation and the other physical parameters were assigned default values. It was observed that the maximum error in the sizes of the traversable objects was 18 % of the body length of the robot. It was also found out that the angular velocities of the robots were significantly different for the real and simulated robots. The conclusion is that a training system can be built based on USARSim when the simulated environments involve simple obstacles because there are not significant discrepancies between the basic traversing abilities of the actual robots and those of the simulated robots.

We have developed a positioning system that uses a phased array sensor to measure the distance and direction of multiple landmarks relative to the position of a mobile robot so that the robot can self-localize. The positioning system can control the strength and the width of the beam from the phased array sensor and observe the multiple landmarks at the same time. By using the distance and direction of plural landmarks, our positioning system is able to use various self-localizing methods. A main part of our work has been incorporating our various techniques for making a robot positioning error smaller into a system in which the most suitable self-localizing method is selected on the basis of sensitivity, which is defined as the ratio between localizing and sensor errors. We propose using a set of indices to evaluate the accuracy of self-localizing methods. The indices are derived from the sensitivity. We used these indices to compare the accuracy of three methods for the self-localizing of a mobile robot using landmarks, and we demonstrated a rational way to minimize a localizing error.

In this paper we describe our work in integrating the results of two previous researches carried on on two different robots. Both robots are designed to help human operators in rescue missions. In the first case, a wheeled robot has been used to develop some software modules. These modules provide the capabilities for autonomously explore an unknown environment and build a metric map while navigating. The second system has been designed to face more challenging scenarios: the robot has tracks and flippers, and features a semi-autonomous behavior to overcome small obstacles and avoid rollovers while moving on debris and unstructured ground. We show how the set of software modules of the first system has been installed on the tracked robot and merged with its semi-autonomous behavior algorithm, and we discuss the results of this integration with a set of experiments.

A tracked mobile robot has high mobility and stability to get over rough terrain by changing its form according to environments. However, it is hard for an operator to control the mechanism skillfully by remote control. One of the solutions of the problem is an implementation of an autonomous control system. A detection of distributed contact points between the crawlers and an environment enable the autonomous control. In this paper, the authors propose a distributed contact sensor for tracked vehicle. In order to apply touch sensors to each track shoe, a problem of electric wirings has to be solved because the crawler is rotating continuously. In our proposed method, contact points are detected by measuring inclination of track shoes optically. For optical sensing of the inclination, a special reflector is designed and evaluated. The authors developed a method for distributed contact sensing of tracked vehicle, and examined whether the sensor can detect contact point during the step climbing motion.

A rescue crawler robot having flipper arm has high ability to get over rough terrain, but it is hard to control its flippers in remote control. The authors aim at development of a semi-autonomous control system for the crawler robot. In the system, moving direction is specified by an operator at remote place. Joypad (Sony PS2 controller) is used as input devise. For increasing its stability and robustness about change of the environment, its flippers are controlled according to sensor informations which can be obtained in real-time. Concretely, the robot recognizes the environment (upward step or downward step) using its physical model, its postural information, flippers' contact and distance between the body and ground, and controls these flippers. In this movie, we show you performance of our proposed control method using "Aladdin".

A rescue crawler robot with flipper arms has high ability to get over rough terrain, but it is hard to control its flipper arms in remote control. The authors aim at development of a semi-autonomous control system for the solution. In this paper, the authors propose a sensor reflexive method that controls these flippers autonomously for getting over unknown steps. Our proposed method is effective in unknown and changeable environment. The authors applied the proposed method to Aladdin, and examined validity of these control rules in unknown environment.

"IRS Souryu" is snake-like robot that is used for victim search in narrow space. We aim at development of multi camera system for "IRS Souryu" and display of wide view angle image for controlling it and searching for victims by using the multi camera system. Advantages of our developed multi camera system are that 1. The number of cameras can be increased by adding multi camera module, 2. Multi camera module is small and has 4 small-size CMOS cameras, and 3. Length of cable can be extended easily because of use of Ethernet. In this paper, we describe concept of acquisition and display of wide view-angle visual information using the multi camera system. We explain composition of multi camera system and its installation on IRS Souryu. We performed an experiment of victim searching by IRS Souryu equipped with 32 cameras. An operator was able to find a victim without extra movement of the robot. Then, the operator was also able to find the next open space to move. We explain the details of the experiment.

In this paper, we summarize the findings and know-hows in the individual developments and try to establish guidelines of human-interface design of rescue robots. These guidelines would be useful for the future development of rescue robots. Preliminary guidelines were set from some case studies of the DDT project and RoboCup Rescue. A trial towards the standardized interface is also shown.

Our research objective is Simultaneous Localization and Mapping (SLAM) in rubble environment. The map construction requires estimation of robot trajectory in 3D space. However, it is hard to estimate it by using odometry or gyro in rubble. In this paper, the authors proposed real-time SLAM based on 3D scan match. 3D camera is used for measurement of 3D shape and its texture in real-time. 3D map and robot trajectory are estimated by combining these 3D scan data. ICP algorithm is used for the matching method. The authors modified ICP algorithm as fast and robust one for real-time 3D map construction.

Intelligent rescue systems with high information and robot technology have been expected to mitigate disaster damages, especially in Japan after the 1995 Hanshin-Awaji Earthquake. In development of robots for search and rescue tasks it is important to develop a robot which can actually work in a real disaster site. Several robots were used for the search and detection operation in the collapsed World Trade Center building in September 2001. From 2002 "Special Project for Earthquake Disaster Mitigation in Urban Areas" (5 yeras project) launched by Ministry of Education, Culture, Sports, Science and Technology, Japan. It aims at significant mitigation the earthquake disaster damage on the scale of the Great Hanshin Earthquake, in densely populated areas in big city regions such as Tokyo metropolitan area and Keihanshin area. In this paper, we introduce the activities of the mission unit on the information collection by on-rubble mobile platforms.

A new phase contrast imaging system that permits a quantitative observation of phase distribution of a general object is proposed and experimentally demonstrated. This is realized by implementing the phase shifting technique in the phase contrast imaging system. A dye-doped nematic liquid-crystal (NLC) is newly employed for this purpose as a variable phase filter in contrast to the constant phase plate employed in the conventional phase contrast microscope (PCM). The dye-doped NLC provides a practical advantage to the system that realizes an alignment-free optical system for the phase plate. The self-alignment property of the phase filter is realized by utilizing the local phase transition from the liquid-crystal to liquid, which is induced by the relatively strong incident light of the specular component of the object. In the experiment, the fundamental phase modulation property and the response of phase modulation ability were measured as a function of incident power of light. Next, the phase measurements were performed with several phase gratings and composite objects having different phase amplitudes and absorption. As an experimental result, the usefulness of the proposed method was confirmed, and the accuracy of the phase measurement was estimated to be λ/40. In addition, it was also demonstrated that the phase information could be obtained independently from the absorption component of the object.

The authors aim at map based outdoor navigation of a mobile robot. In navigation, robot position is fundamentally obtained by odometry. However, the position is misaligned as the robot moves because odometry has cumulative error. DGPS measurement data may cancel its position error. The framework of EKF is used for the modification and the fusion between odometry and DGPS measurement data. The DGPS measurement data, however, could have large error because of multipath near buildings. In this paper, the authors propose a method which eliminates erroneous DGPS measurement data when odometry robot position is fused, and confirm the validity of this approach.

The final objective of the authors is to realize mobile robot navigation in walkway of outdoor environment. The path along the walkway which is measured correctly together with landmarks must be given in the framework in this paper. The robot identifies its position by means of odometry, DGPS and laser range finder (LRF) during the motion along the path. This work contributes to the map building of landmarks along the walkway. To make the map, RTK-GPS, odometry and LRF are used for the sensory devices and Kalman smoothing technique is also incorporated to interpolate trajectory of the scanning LRF equipment between the two point that RTK-GPS measurement took place. The scanning by LRF is performed to acquire the 3-D shape of objects along the walkway. The trajectory presumed properly and well organized shapes of the objects are reconstructed.

This paper describes a strategy of a mobile robot walkway following using color image. There are different colors in a walkway and lawn area alongside the walkway. The walkway area is extracted by an image processing. Color difference among walkway and waysides is considered in the image processing. Robustness against daylight change for segmentation of walkway area is also considered. The robot moves to the direction toward vanishing point of the walkway which is obtained from the image processing. Repeating these processes, the walkway following can be accomplished.

This paper describes a strategy of a mobile robot walkway following using color image. There are different colors in a walkway and lawn area along side the walkway. The walkway area is extracted by an image processing using the difference of color. The robot moves to the direction of vanishing point which is obtained from the image processing. Repeating these processes, the walkway following will be accomplished.