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Author: search.filters.author.Kuchii, Shigeru

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    Traffic Light and Crosswalk Detection and Localization Using Vehicular Camera
    (2022-01-01)
    Wangsiripitak, Somkiat
    ;
    Hano, Keisuke
    ;
    Kuchii, Shigeru
    An improved convolutional neural network model for traffic light and crosswalk detection and localization using visual information from a vehicular camera is proposed. Yolov4 darknet and its pretrained model are used in transfer learning using our datasets of traffic lights and crosswalks; the trained model is supposed to be used for red-light running detection of the preceding vehicle. Experimental results, compared to the result of the pretrained model learned only from the Microsoft COCO dataset, showed an improved performance of traffic light detection on our test images which were taken under various lighting conditions and interferences; 36.91% higher recall and 39.21% less false positive rate. The crosswalk, which is incapable of detection in the COCO model, could be detected with 93.37% recall and 7.74% false-positive rate.
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    Performance Measurement of Energy Optimal Path Finding for Waste Collection Robot Using ACO Algorithm
    (2022-01-01)
    Tomitagawa, Koki
    ;
    Anuntachai, Anuntapat
    ;
    Chotipant, Supannada
    ;
    Wongwirat, Olarn
    ;
    Kuchii, Shigeru
    Indoor waste collection that utilizes mobile robots can solve the labor cost and manpower shortage but has the problem of limited energy resources, making it difficult to operate for long periods of time. Therefore, it is important to reduce the energy consumption for efficient waste collection. The waste collection robot can be modeled as a Capacitated Vehicle Routing Problem (CVRP), where heuristics algorithms can be deployed to search for the most energy-efficient path. This paper proposes the Ant Colony Optimization (ACO) algorithm for finding the optimal path of the waste collection robot. Energy consumption of the robot depends not only on the travel path but also on the weight of the waste it carries. Therefore, the proposed ACO algorithm utilizes the path distance and waste weight as the visibility. The travel distance and energy consumption are also used to determine the updated pheromone. Whereas the conventional and adapted ACO algorithms use only either the path distance or the waste weight as the visibility, respectively. The simulation experiments are conducted to compare the travel distance and the energy consumption that the waste collection robot takes by using the conventional, adapted, and proposed ACO algorithms. In the simulation experiments, the number of nodes, the waste weight, and the carrying capacity are used as parameters to verify the performance under the determined environment. The simulation results express that the proposed ACO algorithm provides a better energy optimal path in terms of travel distance and energy consumption than the conventional and adapted ACO algorithms.
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    Adapted ACO Algorithm for Energy-Efficient Path Finding of Waste Collection Robot
    (2022-01-01)
    Tomitagawa, Koki
    ;
    Anuntachai, Anuntapat
    ;
    Chotiphan, Supannada
    ;
    Wongwirat, Olarn
    ;
    Kuchii, Shigeru
    Waste collection is a major concern of many companies with large areas of facility, e.g., buildings or factories, where there are many trash bins at various dumping points. Therefore, they require human labor to handle, which is a major cost of consideration. Currently, there are research works using robots for waste collection instead of humans. There is a challenge for waste collection robots in terms of energy consumption to pick up the waste at various dumping points efficiently. The factors related to the energy consumption of waste collection robots are directly related to the distance and waste weight that the robots have to collect and carry from the trash bins at various dump points along the paths. This paper presents the adapted ant colony optimization (ACO) algorithm to find the energy-efficient paths of the waste collection robots. The adapted ACO algorithm uses the waste weight in the trash bin as path heuristic information between two dumping points to determine the state transition probability for finding the most energy-efficient path. The experiment was conducted by the simulation to compare the result with the conventional ACO algorithm that uses distance as the path heuristic information. The simulation results expressed that the adapted ACO algorithm provided the most energy-efficient path under the number of nodes and waste weights specified better than the conventional ACO algorithm.
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    Energy optimal path finding for waste collection robot using ant colony optimization algorithm
    (2021-01-01)
    Tomitagawa, Koki
    ;
    Chotiphan, Supannada
    ;
    Kuchii, Shigeru
    ;
    Anuntachai, Anuntapat
    ;
    Wongwirat, Olarn
    Solid Waste Management (SWM) has always been an important consideration for any country, and among the operational steps of SWM, Solid Waste Collection (SWC) has become one of the most challenging ones. Currently, most of the vehicles used for waste collection require workers and have the problem of emitting CO2. Compared to waste collection by vehicles, waste collection using mobile robots has the advantage of not consuming personnel and not emitting CO2, which is harmful to the environment. However, while mobile robots can solve the shortage of manpower and environmental problems, they also have the problem of limited energy resources. In order for mobile robots to collect waste more efficiently, we designed the waste collection problem as a Capacitated Vehicle Routing Problem (CVRP) and optimized it using the Ant Colony Optimization (ACO) algorithm. The ACO algorithm proposed in this study focuses on the energy consumption of the mobile robot performing waste collection and searches for a route with less energy consumption by using the waste weight as the weighting factor. The preliminary performance verification of the proposed method is compared with the existing conventional ACO algorithm using the CVRP benchmark.
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    Reserch and development of the city commuter installed ICT functions in consideration of usability
    (2015-01-01)
    Okumura, Kohei
    ;
    Sararuengpong, Kitipat
    ;
    Chaweechan, Charoen
    ;
    Ishida, Koji
    ;
    Ishigami, Kazuyuki
    It is commonly believed that the development of ICT contributes in various fields. Accordingly, the Ministry of Internal Affairs and Communications of Japan has promoted «ICT community development business». In local area where does not have enough public transport facilities, it is hard for elderly people who cannot drive a car to go out. Additionally, it is supposed that the time national disasters like earthquakes happen all of transport would be stopped. To solve these problems is the one of the goal of the business, and we research and develop a vehicle called city commuter that has convenience ICT functions. Its design is based on three-wheeled electric bicycle. This paper shows the way we decided the design of the city commuter. After that, it explains the detail of the method to create each ICT system. At the end, it describes the conclusion and the future prospects of this study.