Kiyohiko Hattori

Hybrid Indoor Location Estimation System Using Image Processing and WiFi Strength

Recently, the service of cellular phone which is dependent on the location is spreading widely. Various techniques are suggested for the location estimation in indoor, however, indoor location estimation techniques have many subjects with a cost and an aspect of the accuracy. To deal with these subjects, we propose a quite new hybrid indoor location estimation method for paying attention to a smart phone with built-in wifi and camera. The proposal method is able to realized both highly accuracy of indoor location estimation and low cost by using the two-dimensional marker, wifi base stations, and the radio wave strength of adhoc communications. Verified by using simulation was able to demonstrate the effectiveness.

Multiagent-based ABC algorithm for Autonomous Rescue Agent Cooperation

This paper focuses on cooperation among autonomous rescue agents in dynamic disaster environments, proposes Multiagent-based Artificial Bee Colony (M-ABC) algorithm by improving ABC algorithm without using global information (i.e., local information only), and investigates its effectiveness from the viewpoint of finding victim quickly and efficiently. The intensive simulations on the victim rescue in RoboCup Rescue Simulation System (RCRSS) have revealed the following implications: (1) M-ABC algorithm can rescue victims faster than the full search method as the conventional method. In particular, M-ABC distance (as one of the proposed M-ABC algorithms) can derive the highest performance; (2) M-ABC distance can keep high performance even in dynamical environments where victims move elsewhere; and (3) M-ABC distance can completely rescue victims in dynamical environments, while Ri-one method as the 2012 champion of RoboCup Rescue Simulation League (RCRSL) cannot in such a case.

Improving Recovery Capability of Multiple Robots in Different Scale Structure Assembly

This paper investigates the recovery capability in the distribution control of the multiple robots which may be broken through the simulation of space solar power satellite assembly with changing its scale. For this purpose, we conduct simulations with changing the failure rate of robots that employ our proposed deadlock avoidance method. Through the intensive simulations, we have revealed that (1) the recovery capability of our proposed method is revealed because the upward tendency of our method as increasing of number of robots and (2) the tendency changes when the ratio of broken robots is under 30%, which does not depend on the scale of the SSPS or the number of robots. From these findings, the recovery capability of our method is high without depending on the scale of SSPS so that the cooperation between robots works well in the robots broken case.

Deployment of wireless mesh network using RSSI-based swarm robots

This paper proposes a novel method for deploying a wireless mesh network (WMN) using a group of swarm robots equipped with wireless transceivers. The proposed method uses the rough relative positions of the robots estimated by their Radio Signal Strength Indicators (RSSIs) to deploy the WMN. The employed algorithm consists of three parts, namely, (1) a fully distributed and dynamic role decision method among the robots, (2) an adaptive direction control using the time difference of the RSSIs, and (3) a narrow corridor for the robots to pass by movement function along walls. In our study, we evaluated the performances of the proposed deployment method and a conventional method in a real environment using 12 real robots for simple deployment, and 10 real robots for passing the narrow corridor. The results of the performed experiments showed that (1) the proposed method outperformed the conventional method with regard to the deployment time, power consumption, and the distances traveled by the robots, and (2) the movement function along the walls is effective while passing a narrow corridor unlike any other function.

Hybrid directional-biased evolutionary algorithm for multi-objective optimization

This paper proposes the hybrid Indicator-based Directionalbiased Evolutionary Algorithm (hIDEA) and verifies its effectiveness through the simulations of the multi-objective 0/1 knapsack problem. Although the conventional Multi-objective Optimization Evolutionary Algorithms (MOEAs) regard the weights of all objective functions as equally, hIDEA biases the weights of the objective functions in order to search not only the center of true Pareto optimal solutions but also near the edges of them. Intensive simulations have revealed that hIDEA is able to search the Pareto optimal solutions widely and accurately including the edge of true ones in comparison with the conventional methods.

Dynamic matching range in Exemplar-based Learning Classifier System

This paper proposes the extended version of Exemplar-based Learning Classifier System (ECS) called DMR-ECS which introduces the basis function for the dynamic matching selection in ECS. In comparison with our previous match selection in ECS, the proposed dynamic match selection in DMR-ECS can control an appropriate range of the match selection automatically to extract the exemplars that cover given problem space. Intensive simulation on the cargo layout problem has revealed that DMR-ECS contributes to not only improving the performance but also reducing the number of the exemplars with an appropriate range of the match selection.

Large-Scale Structure Assembly by Multiple Robots Which May Be Broken

This paper investigates how to design the limit of failure rate and the adjust number of robots in the distribution control of the multiple robots which may be broken through the simulation of space solar power satellite assembly. For this purpose, we conduct simulations with changing the failure rate of robots that employ our proposed deadlock avoidance method. Intensive simulations have revealed the following implications: (1) from the viewpoint of the completion rate, our deadlock avoidance method enables the robots to complete the assembly in 80completion rate even if the 1/3 robots are broken; (2) from the viewpoint of the recovery rate (i.e., the rate of completing a task when some of robots are broken), the maximum failure rate which enables robots to complete the assembly in 80% is 0.2%, i.e., the 1/3 robots can be broken; and (3) when the failure rate is 0.2%, it is possible to maximize the completion rate from 80% to 90% by adjust the number of the robots.

An implementation of multichannel multi-interface MANET for fire engines and experiments with WINDS satellite mobile earth station

We propose a novel communication system for an emergency fire response team, which provides Internet service on the way to and in the disaster area. The system is composed of a multi-interface mobile ad-hoc network (MANET) router, a Global Positioning System (GPS) receiver, and two Wi-Fi interfaces with directional antennas, which can be easily attached to the roof of a vehicle. The front-side Wi-Fi interface of the vehicle is operated in the infrastructure mode, and the rear-side interface is operated in the access point mode. Different channels are assigned to each AP interface of the vehicles. Infrastructure-mode Wi-Fi interfaces automatically scan and connect to an appropriate AP interface and create MANET links. Some experiments using this wireless system with the WINDS satellite mobile earth station and nine fire engines were conducted in Ebetsu, Hokkaido. We measured the TCP throughput and confirmed that a throughput of more than 10 Mbps was able to be obtained by most of the node pairs. In addition, high-vision video streaming was able to be successfully transmitted to the streaming server on the Internet through MANET and satellite communication links while they were platooning.

Urban Disaster Simulation Incorporating Human Psychological Models in Evacuation Behaviors

Building evacuation simulation provides us with various knowledge and suggestion before a real disaster happens. To date, however, evacuees were often modeled as homogeneous without individual motivation in a large-scale urban simulation model, which is rather different from real human behavior. In this paper, an evacuation simulation model with human psychological models is developed for urban disaster situation. Three psychological models are actually incorporated: normalcy bias, emotional contagion bias, and sympathy behavior bias. Normalcy bias is the initial evacuation delay caused by a belief that abnormal events rarely happen. Emotional contagion is the effect of one person’s emotional state on the emotional state of people around him/her both explicitly and implicitly. Simulated experimental results show that the proposed model provides accurate evacuation behaviors than the normal behavior model without psychological consideration.

Multi-objective Optimization for Common and Special Components: First Step Toward Network Optimization of Regular and Non-Regular Flights

To optimize the problem composed of (i) the common components which should be optimized from the viewpoint of all objective functions and (ii) the special components which should be optimized from the viewpoint of one of the objective functions, this paper proposes a new multi-objective optimization method which optimizes not only the common components for all objective functions but also the special ones for each objective function. To investigate the effectiveness of the proposed method, this paper tested our method on the test-bed problem which is an extended version of the 0/1 knapsack problem. The intensive experiments have revealed the following implications: (i) Our method finds better solutions which have higher fitness than the conventional method (NSGA-II); (ii) our method can find the solutions that had a large norm (which corresponds to a high profit of an airline company in the flight scheduling problem) with the high rate of the common components; and (iii) since the crowding distance employed in our method contributes to keeping the diversity during the solution search, our method has high exploration capability of solutions.