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The research in environmental robotics, ubiquitous robotics, and network robots aim to create intelligent environments for providing various services by gathering, managing, and supplying information via distributed communication, sensing, and actuation. Various applications of such robotic systems have been proposed and studied, e.g. life support (Sato et al., 1996), environmental monitoring and information management (Parker et al., 2003; Low, 2004; Tang, 2004), task assignment (Batalin & Sukhtame, 2003), and rescue operation (Kurabayashi et al., 2001; Tadokoro et al., 2003; Miyama et al., 2003). These applications employ various navigation methods addressed in numerous publications (Borenstein et al., 1996; Arai et al., 1996b; Li et al., 2003; Parker et al., 2003; Nakamura et al.; 2003). This chapter introduces a cooperative navigation method for multiple mobile robots operating in indoor environments, as an example of our research work in intelligent environmental robotic systems. The method relies on the information management about the environment, namely, static global information and local information. The former is represented by a topological map (Mataric, 1992) that displays the positional relation from any starting point to any goal point and is relevant for planning a route. The latter contains a map of the local environment and the traffic information for dynamic navigation. The proposed navigation method makes use of an Information Assistant (IA) – a communication device embedded into the environment. The IA updates and manages information about the local environment and communicates with the robots. The navigation also relies on an Optical Pointer (OP) to guide robots at intersections by means of projecting a laser light onto the ground. The OP communicates with the robot via the IA, when indicating target positions to the robot. The mobile robot detects a laser beacon on the ground by means of image processing and moves towards the beacon. When the robot reaches the proximity of the beacon, the next sub-goal is indicated, and the laser beacons lead the robot along the route. The IA and OP devices assist the robot to navigate in the environment, which can be unknown to the robot. In contrast with other navigation methods, where the robot attempts to process all the information available about the environment, e.g. simultaneous localization and mapping (Smith et al., 1990; Choset & Nagatani, 2001) or an improved topological map (Tomono &

We propose a multiple-mobile sensor node (MSN) deployment strategy that considers wireless communication quality and operation time of underground wireless sensor networks. After an underground disaster, it is difficult to perform a rescue operation because the internal situation cannot be confirmed. Hence, gathering information using a teleoperated robot has been widely discussed. However, wireless communication is unstable and the corresponding wireless infrastructure to operate the teleoperated robot is unavailable underground. Therefore, we studied the disaster information-gathering support system using wireless sensor networks and a rescue robot. In this study, the movement path information of the teleoperated robot is fed to MSNs in a graph structure. MSNs are deployed in the underground environment by adding an evaluation of communication quality and operation status to a given graph structure. The simulation was evaluated in an assumed underground environment. The results confirmed that the wireless communication quality between each MSN was maintained and energy consumption was balanced during the deployment.

This paper presents an automatic convergence estimation method for the reinforcement learning (RL) of autonomous agents. Recently, a multi-agent robot system (MARS) that uses an RL algorithm has been studied in real-world situations. This system can obtain behaviors autonomously through multi-agent reinforcement learning (MARL). However, MARL takes a long time to obtain an optimal or near-optimal solution. Furthermore, the agents continued learning after obtaining of the solution may lead to overfitting. It is difficult for the MARL operator to determine whether the learning has been converged or not, because the operator has to determine the convergence of all learning agents. The convergence of the learning curve indicates that knowledge has been obtained. However, judging the convergence of RL depends on human intuition and experience, and few studies have discussed convergence estimation methods. Therefore, in this paper, we address development of an automatic convergence estimation method that does not require human judgement. In prior work, we proposed automatic convergence estimation method using fractal dimensional analysis which evaluates the learning curve of the learner as agents, and we confirmed the effectiveness of our previous method by conducting a computer simulation. In this study, we propose a method based on fractal dimensional analysis considering implementation to the robots and evaluate the effectiveness of the method by using an expanded experimental setup that considering a computer simulation and an actual mobile robot environment.

This paper proposes an automatic policy selection method using spreading activation theory based on psychological theory for transfer learning in reinforcement learning. Intel-ligent robot systems have recently been studied for practical applications such as home robot, communication robot, and warehouse robot. Learning algorithms are key to building useful robot systems important. For example, a robot can explore for optimal policy with trial and error using reinforcement learning. Moreover, transfer learning enables reuse of prior policy and is effective for environment adaptability. However, humans de-termine applicable methods in transfer learning. Policy selection method has been proposed for transfer learning in reinforcement learning using spreading activation model proposed in cognitive psychology. In this paper, novel activation function and spreading sequence is discussed for spreading policy selection method. Fur-ther computer simulations are used to examine the effectiveness of the proposed method for automatic policy selection in simplified shortest-path problem.

This paper describes a perilous environment estimation system involving the use of a teleoperated rescue robot with on-board LiDAR supported by a human teleoperator to avoid mis-operation and effectively inspect the perilous environment. Teleoperated rescue robots have been deployed recently in actual disaster-stricken areas, and the performance of the rescue robots is also improving. However, some incidents such as the robot being stuck in an obstacle tend to occur. Not only does this prevent the robot from returning, but the stuck robot may also become a new obstacle in the disaster area. In situations involving mis-operations, utilizing failed operational experiences is important when the operator undergoes training related to teleoperation skills, and it is also effective for actual disaster situations. In this paper, we propose a storing method for perilous environments and an estimation method between stored perilous environmental information and current measured information by using a histogram intersection method. In this system, the environmental information is described as a point cloud that is obtained from the LiDAR on-board the robot. Further, using mock-up stairs, the effectiveness of the proposed method in estimating the perilousness of the current environmental information based on the perilous environment as measured from the stored environments is confirmed.

In this paper, a distributed collective movement control method is proposed for a swarm robotics system based on an internal energy thermodynamic model. The system can move between obstacles with a changing aggregation suitable for confronting obstacle arrangements in an environment. The swarm robot shape is a fixed aggregation formed by virtual attraction and repulsion forces based on the proposed method. It follows a leader agent while retaining its shape. When the swarm robot aggregation shape cannot be maintained during movement though narrow spaces with obstacles, the swarm robot flexibly changes shape according to that of the local environment. To this end, it employs virtual thermal motion, which is made possible with directives and enables continuous movement. A simulation confirmed the capability of the proposed method in enabling the solidity and flexibility collective movement of swarm robots. The results furthermore showed that the parameter setting range is important for applying the proposed method to collective movement.

These days, web applications are widely used on not only desktop PCs but also tablet PCs and smartphones. For developers of web applications, productivity and effectiveness (usability and accessibility) are big issues to respond to customers’ high expectations for web applications. This paper focuses on the development of business use web by system engineers and programmers, and proposes a design framework featuring usability/accessibility guidelines, UI (design) patterns, which connect usability/accessibility guidelines, sample programs, and some other components. The framework aims at high flexibility, productivity, and effectiveness (usability and accessibility) for various developments of business use webs.

This paper presents a framework, called the knowledge co-creation framework (KCF), for the heterogeneous multi-robot transfer learning method with utilization of cloud-computing resources. A multi-agent robot system (MARS) that utilizes reinforcement learning and transfer learning methods has recently been deployed in real-world situations. In MARS, autonomous agents obtain behavior autonomously through multi-agent reinforcement learning and the transfer learning method enables the reuse of the knowledge of other robots’ behavior, such as for cooperative behavior. These methods, however, have not been fully and systematically discussed. To address this, KCF leverages the transfer learning method and cloud-computing resources. In prior research, we developed a hierarchical transfer learning (HTL) method as the core technology of knowledge co-creation and investigated its effectiveness in a dynamic multi-agent environment. The HTL method hierarchically abstracts obtained knowledge by ontological methods. Here, we evaluate the effectiveness of HTL with two types of ontology: action and state.

We are working to develop an information gathering system comprising a mobile robot and a wireless sensor network (WSN) for use in post-disaster underground environments. In the proposed system, a mobile robot carries wireless sensor nodes and deploys them to construct a WSN in the environment, thus providing a wireless communication infrastructure for mobile robot teleoperation. An operator then controls the mobile robot remotely while monitoring end-to-end communication quality with the mobile robot. Measurement of communication quality on wireless LANs has been widely studied. However, a throughput measurement method has not been developed for assessing the usability of wireless mobile robot teleoperation. In particular, a measurement method is needed that can handle mobile robots as they move around an unknown environment. Accordingly, in this paper, we propose a method for measuring throughput as a measure of communication quality in a WSN for wireless teleoperation of mobile robots. The feasibility of the proposed method was evaluated and verified in in practical field test where an operator remotely controlled mobile robots using a WSN.

The results of neurophysiological research have indicated the important role of neuromodulation in behavior decisions during fighting between male crickets. To understand such a dynamic behavior generation mechanism, we attempt to construct a neuromodulation model of behavior selection for the fighting behavior of a cricket. In this paper, we propose a dynamic system model of neuromodulation with the efficacy based on neurophysiological knowledge, facts, and hypotheses from the viewpoint of synthesis. The efficacy of the sensory processing center is introduced to our previous model and its dynamics is influenced by the frequency of the interactions with the other cricket. Utilizing an extended neuromodulation model, computer simulations related to a multiple-individual environment were carried out, and the results are discussed. In particular, the properties related to the standard deviation of the value of octopamine in several population density cases are discussed.

In this paper, we propose a method of estimating amount of attitude change of stationary sensor node which is important to realize observation of identical spot for a long term based on the tracked position data of underwater landmark generated on underwater image, and then in order to see a target, in here a coral, in the fixed position on image, attitude of captured image is corrected based on the estimated amount of attitude data. Then, we generate underwater landmark based on orientation code which is robust for illumination change caused by wave, and track underwater landmarks sequentially combining the method of position detection by using orientation code matching and the method of position estimation by particle filter. Further, we design the evaluation function using time series images. Then, we estimate amount of attitude change of sensor unit of stationary sensor node by optimizing the evaluation function based on Steepest Descent Method, and correct the attitude of original image with the estimated attitude data. Finally, through some experiments, we prove the effectiveness of our methods and discuss the future work.

In recent years, it says that the number of the coral decreases by the change in the marine ecosystem, the change of marine environment and increase of crown-of-thorns starfish. Therefore, the research and preservation of coral is necessary urgently. Then, authors have been developing the device which is called the stationary sensor node to observe underwater environment with wide range for a long term. In order to measure identical spot with the device, it is necessary to grasp its attitude data of stationary sensor node and observe the coral in the fixed position. However, it is difficult to grasp all of information by internal sensor of stationary sensor node. In this paper, we introduce a method of position measurement of marine tag which is defined as landmark on underwater image. Further, we show a method to estimate the attitude data based on position data of marine tag.

市販輸入加工食品10試料を小売店で購入し(株)ロート製薬製のイムノクロマトを用い,特定原材料5品目の含有の有無を定性的に判定した.また同時に同一試料について(株)森永生科学研究所製のELISAキットを用いて5品目の定量を行い,両結果を比較し,イムノクロマトの有用性を調べた.イムノクロマトの測定が困難であったかりんとう以外のビスケット,ポテトチップス,チョコレート,キャラメル,ケーキ,冷麺ナッツ菓子,えびせんべい及びアイスクリームではイムノクロマト法で偽陽性が若干見られたが,全体的には良好な相関性が認められ,ELISAで10μg/g以上含む特定原材料は全て簡易に検出できた.従ってイムノクロマト法は市販加工食品についても特定原材料含有の有無の簡易なスクリーニング法として有用であることが判明した.

We detail an omnidirectional mobile platform for research and development (R&D). In 1995, we reported that a special driving mechanism for holonomic omnidirectional mobile robots was designed to enable 3 degree of freedom (DOF) motion control by 3 corresponding actuators decoupled with no redundancy. We constructed a omnidirectional mobile robot prototype with a drive. We took part in a RoboCup tournament as Uttori United with omnidirectional mobile robots: ZEN-450, using our driving mechanism, in 1997, and 2000. ZEN-450 showed high mobility during the tournament However, unpredictable problems occurred because ZEN-450 is not developed for robotic soccer. , We considered improving its hardware as a platform. We report the new platform and test-running results.

This paper describes the underwater data collection utilizing stationary sensor node and movable sensor node. We consider applying the system to investigate the conditions of marine ecosystem around the coral reef at Okinawa, Japan. The framework and fundamental design of our proposed underwater information gathering system under development are introduced. It is also reported the development of the prototypes of the sensory node and movable sensor node. Basic examinations utilizing such prototype at underwater environment are also described. This paper also describes experimental results of image gathering from via wireless local area network communication. Our future trials based on the current developmental situation are also discussed.

In recent years, many researchers try to observe the state of the global environment from marine information. In this paper, we introduce the recording system of underwater environment. By using this system, we want to observe the change of global environment from the coral bleaching. Especially, we propose the generation method of marine tag in order to measure the 3D position of robot which is used in the sea for measure state of coral bleaching. Marine tag means the feature point of underwater image.

In this paper, we propose temporary rest facilities information exchange system among many people unable to get home by utilizing Delay Tolerant Network (DTN) after a disaster. When public transportation services are interrupted by the disaster, those people try to get home on foot while taking a rest at the facility. However, it is difficult for those people to obtain information of temporary rest facilities provided hurriedly, because communication infrastructures in the disaster area are disconnected by the disaster damage. Therefore, we propose a method to exchange the information among those people mutually by using mobile device via DTN for diffusion of the information. By using DTN, those people can communicate with each other by using mobile device and use the rest facility on the basis of the information even if the communication infrastructures are disconnected. Then, we develop mobile device application software to exchange the rest facility information among the people via DTN. In order to evaluate the application, we verified the communication performance in practical experiments. The experimental results showed the developed application had sufficient performance to exchange the information of the rest facility via DTN. Then, we verify the diffusivity of the rest facility information by a network simulation. The simulation results showed that the rest facility information was diffused widely and effectively to those people.

We propose Robot Wireless Sensor Networks (RWSNs) management method for maintaining wireless communication connectivity for a mobile robot teleoperation with considering a distance between sensor nodes. Recent studies for reducing disaster damage focus on a disaster area information gathering in underground spaces. Since information gathering activities in such post disaster underground spaces present a high risk of personal injury by secondary disasters, a lot of rescue workers were injured or killed in the past. On basis of this background, gathering information by utilizing the mobile robot is discussed in wide area. However, maintaining wireless communication infrastructures for teleoperation of a mobile rescue robot in the post-disaster underground space by various reasons. Therefore we have been discussing the wireless communication infrastructures construction method for teleoperation of the rescue robot by utilizing the RWSN. In this paper, we evaluated the proposed method for changing routing path by utilizing the RWSN in field operation test in order to confirm the availability of performance of communication connectivity and the throughputs between End-to-End communications via constructed network.

This paper presents a framework, called the knowledge co-creation framework (KCF), for heterogeneous multiagent robot systems that use a transfer learning method. A multiagent robot system (MARS) that utilizes reinforcement learning and a transfer learning method has recently been studied in realworld situations. In MARS, autonomous agents obtain behavior autonomously through multi-agent reinforcement learning and the transfer learning method enables the reuse of the knowledge of other robots’ behavior, such as for cooperative behavior. Those methods, however, have not been fully and systematically discussed. To address this, KCF leverages the transfer learning method and cloud-computing resources. In prior research, we developed ontology-based inter-task mapping as a core technology for hierarchical transfer learning (HTL) method and investigated its effectiveness in a dynamic multi-agent environment. The HTL method hierarchically abstracts obtained knowledge by ontological methods. Here, we evaluate the effectiveness of HTL with a basic experimental setup that considers two types of ontology: action and state.

We propose a wireless sensor networks deployment strategy for constructing wireless communication infrastructures for a rescue robot with considering a throughput between sensor nodes (SNs). Recent studies for reducing disaster damage focus on a disaster area information gathering in underground spaces. Since information gathering activities in such post disaster underground spaces present a high risk of personal injury by secondary disasters, a lot of rescue workers were injured or killed in the past. Because of this background, gathering information by utilizing the rescue robot is discussed in wide area. However, there are no wireless communication infrastructures for tele-operation of rescue robot in the post-disaster environment such as the underground space. Therefore, we have been discussing the construction method of wireless communication infrastructures for remotely operated the rescue robot by utilizing the rescue robot. In this paper, we evaluated the proposed method in field operation test, and then it is confirmed that maintaining communication connectivity and throughputs between End to End of constructed networks.

This manuscript reported basic examination results of the wireless network communication performance at the coast. We consider that underwater environment condition monitoring is a sort of likely typical application for ubiquitous sensor networks. The result of the experiment shows the performance of the wireless network communication at the coastal area.

An adaptive multirobot scheduling system was studied in order to introduce intelligent robots in a plant and to maintain the plant effectively. Necessary information for the plat maintenance tasks was classified by character that are a variable and a fixed information. In order to assign maintenance tasks to the robots, the scheduling system uses the fixed information of own databases, and gathers the variable information from the robots and a human operator adaptively. From numerical experiments it has been confirmed that the adaptive scheduling system could perform its original idea of adjusting the scheduling of maintenance operation even when an accident occurred in the plant or when a robot was disabled.

This paper proposes a novel man-machine interface which takes into account the mutual cooperation between the operator and an expert system in order to realize precise decision making and operation. This interface is composed of three modules: a diagnosis module, a supporting module for the operator's decision making and an indication module. The knowledge base in the system described is represented by a fault tree diagram, incorporated to communicate between the operator and the computer. The system constructed enables the diagnosis of not only human errors, but also malfunctions of the process, and increases precision, reliability, and safety during bioprocess operation.

In this paper, we propose a spectrum sharing between multi-hop inter vehicle communication (IVC) and road-vehicle communication (RVC) in multi-hop vehicular cognitive radio. In spectrum shared multi-hop vehicular networks, each link has different signal to noise ratio (SNR) because of different distance of vehicles and avoiding interference toward a primary user (PU). In addition, since a vehicle has high mobility, SNR is dynamically changed in a short time. Therefore, the end-to-end throughput is fluctuated in a short time and it is difficult to establish stable communication by using multi-hop wireless networks. In order to solve this problem, we propose a utilization of vehicle mobility information (e.g. position, direction, and speed) to predict the link throughput of multi-hop networks with sharing the spectrum with PU. The spectrum of each link is assigned by using the result of throughput prediction of the end-to-end links. By using computer simulations, we confirm the effectiveness of the proposed method in term of end-to-end throughput.

We propose a rescue robot sensor network system in which a teleoperated rescue robot sets up a wireless sensor network (WSN) to gather disaster information in post-disaster underground spaces. In this system, the rescue robot carries wireless sensor nodes (SNs) and deploys them between gateways in an underground space on demand by the operator’s command to establish a safe approach path before rescue workers enter. However, a single communication path only is setup, because the rescue robot linearly deploys SNs between gateways. Hence, the rescue robot cannot be operated remotely if the communication path is disconnected by, for example, SN failure or changes in the environmental conditions. Therefore, SNs must be adaptively deployed so as to maintain WSN communication connectivity and negate such situations. This paper describes an SN deployment strategy for construction of a WSN robust to communication disconnection, caused by SN failure or deterioration of communications quality, in order to maintain communication connectivity between SNs. We thus propose an SN deployment strategy that uses redundant communication connection and ensures communication conditions between end-to-end communications of the WSN. The proposed strategy maintained communication conditions such that throughput between end-to-end communications in the WSN. Experimental results verifying the efficacy of the proposed method are also described.

Japan is a land of frequent earthquakes, and developing effective means for preventing and mitigating disasters in their aftermath is a matter of deep and widespread concern. The time and location of their occurrence is essentially unpredictable, and interest therefore centers on preventing and mitigating damage. A key prerequisite for effective mitigation is rapid, accurate appraisal of conditions in the stricken region. For this purpose, the development of systems for concurrent, parallel information gathering, capable of covering a broad range of affected areas and conditions, is critical. In the DDT Project, 'Development of Advanced Robots and Information Systems for Disaster Response.' of the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), the development effort for rescue robots and other next-generation basic technologies for disaster prevention and mitigation has included the development of interlinked rescue robots, airborne vehicles, sensors, and other elements of disaster area information gathering technologies (Tadokoro, 2009). A related recent development has been the trend toward ubiquitous computing (Weiser, 1991), data carriers (Takeda, 1991), and related technologies, with research and development in progress for the creation of intelligent information environments to support and aid in daily life and living. In parallel with these advances, the authors have developed an intelligent data carrier (IDC) for rescue, designed to support the search for victims immediately after an earthquake (Kurabayashi et al., 2003); (Asama et al., 2005); (Kawabata et al. 2006); (Hada et al., 2006). The rescue IDC is a small device with wireless radio communication capability, for installation in living environments. In the wake of an earthquake, this device can send out voice calls to any who might be trapped in the rubble and record their responses. With multiple deployments, the IDCs enable parallel searches for victims throughout the stricken area. In a separate study, Takizawa et al. (2007) has applied RFID (Radio Frequency Identification) technology to the development of an information transmission system in which wireless tags are permanently installed along streets and other routes to collect information on the stricken area, so that victims trying to leave the area and rescue personnel can perform non-contact automated gathering of the information. In the wake of a disaster, however, the rescue IDCs may not be available where