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Integration of Drone’ Communication into an ITS Network Integration of Drone’ Communication into an ITS Network $15.00

Satoshi Fujii, Kodai Hiranaka, Seichiro Miyagi, and Zacharie Mbaitiga

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National Institute of Technology, Okinawa College, japan

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Vol. 3, Issue 2

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89-91

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29-12-2017

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Abstract: This paper presents the concept of a highly-sophisticated network system using unmanned aerial vehicles, further named drones, and wireless networks for enhancing safety against natural disasters. The system consists of several drones and ground vehicles. Each vehicle has a wireless network unit, which employs the dual-mode Wireless Access in Vehicular Environment (WAVE) in the 700 MHz or 5 GHz band, with the goal of creating a multi-hop (more than three hops) ad hoc network. These features enable the system to facilitate rescue and relief operations in the event of a serious disaster. The proposed system represents an innovation in the field of mesh network systems, being based on a combination of ubiquitous drones and ground vehicles.
LIDAR-based Object Classification for Autonomous Driving on Urban Roads LIDAR-based Object Classification for Autonomous Driving on Urban Roads $15.00

Naoki Suganuma, Masaru Yoshioka, Keisuke Yoneda, and Mohammad Aldibaja

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Kanazawa University

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Vol.3, Issue 2

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92-95

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29-12-2017

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Abstract: Object classification is an important technique for autonomous vehicles to identify surrounding dynamic objects and execute safe path planning. In this paper, a multi-class object classification method is proposed to classify objects around the vehicle into car, pedestrian bicyclist, and background using a LIDAR sensor. The various effective features of each object are computed using 3D point clouds, and Real AdaBoost algorithm is applied for multi-class classification. In addition, class probabilities are calculated and updated in a time series framework for tracking objects. Classification is evaluated using a dataset that includes long-range objects over 50m. The overall accuracy of the clusters for each frame is 92.7% and for tracking objects is 95.5%. Moreover, processing time for object classification is 0.07ms. Thus, this method can be used in real time for autonomous driving on urban roads.
Rapid Human Body Detection in Disaster Sites using Image Processing from Unmanned Aerial Vehicle (UAV) Cameras Rapid Human Body Detection in Disaster Sites using Image Processing from Unmanned Aerial Vehicle (UAV) Cameras $15.00

Zacharie Mbaitiga , Satoshi Fujii, Shimoji Minori

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National Institute of Technology, Okinawa College

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Vol. 3, Issue 2

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96-101

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29-12-2017

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Abstract: The development and impact of technology on our everyday lives cannot be compared with the world our ancestors lived in several decades ago. This is described as the world of technology (WoT). But despite all the advancements in technologies, understanding of the mechanisms of nature and the damages caused via natural disasters, such as earthquakes, landslides, and flooding to mention only a few, are still very far away. In the effort of saving lives during natural disasters, such as earthquakes, this study introduces a rapid human body detection technology using image processing from UAV camera. The skin color from a female student is first extracted in RGB then converted to HSV. Next, opening and closing morphological operations are performed eight times each to remove all noise present in the image. Experimental tests were performed both indoor and outdoor, where the female student presented an object close and far to the camera to check the detection capability in both cases. The experiment results show that close or far, the camera can clearly detect both a human body and any part of a human body. The results of the experiment proves the merit of the proposed method.
Convolutional Neural Network Based Vehicle Turn Signal Recognition Convolutional Neural Network Based Vehicle Turn Signal Recognition $15.00

Keisuke Yoneda, Ryota Hagi, Akisue Kuramoto, Mohammad Aldibaja, Ryo Yanase and Naoki Suganuma

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Kanazawa University

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Vol .3, Issue 2

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102-106

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29-12-2017

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Abstract: Automated driving is an emerging technology in which a car performs the tasks of recognition, decision making, and control. Recognizing surrounding vehicles is vital in generating the trajectory of an ego-vehicle. This paper focuses on detecting a turn signal information as one of the driver’s intention for surrounding vehicles. This information helps to predict the driver’s behavior in advance especially as instances of lane change and turns at an intersection. Using their intension, the automated vehicle is able to generate a safety trajectory before the driver’s behavior changes. The proposed method recognizes the turn signal of the target vehicle using a mono-camera. It detects the lighting state using Convolutional Neural Network, and then calculates a flashing frequency using Fast Fourier Transform.
An Assistive Robotic Arm for People with Severe Disabilities:Evaluation of Eating Soup An Assistive Robotic Arm for People with Severe Disabilities:Evaluation of Eating Soup $15.00

Shotaro Gushi, Hiroki Higa, Hideyuki Uehara and Takashi Soken

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Ryukyu University

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Vol. 3, Issue 2

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107-112

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29-12-2017

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Abstract: An assistive robotic arm for people with severe disabilities is presented in this paper. Its user interface using eye movements consists of a Web camera, computer, and microcontroller with display unit. Using the robotic arm system, we performed two experiments: (1) transferring water task and (2) eating soup task. It was found from the experimental results that the assistive robotic arm system could stably and appropriately transfer more than 82 % of water and 86 % of soup to the respective positions.
Preliminary Assessment for Inshore Fishing UAV (ISFUAV) Preliminary Assessment for Inshore Fishing UAV (ISFUAV) $15.00

Zacharie Mbaitiga and Honda Kyuhei

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National Institute of Technology, Okinawa College

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Vol. 3, Issue 2

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113-119

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29-12-2017

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Abstract: The development and entry into service of unmanned air vehicle (UAV) systems has a long, history. Unfortunately, the vision of engineers and scientist is have seldom matched that of administrators, regulators or financiers. The availability of UAV systems has also often depended upon the maturation of the requisite technology. UAV systems are now being operated by several military forces and currently, to a more limited extent, by civilian organizations. Civilan organizations, however, may eventually expand to exceed, in number and diversity, those of the military [1]. UAV are now use in many domains to perform tasks that may cause risk to human life or in the surveillance of the suicide sites to prevent young people in depression to from committing suicide. UAV are also used to collect information to support decision making during crises, in monitoring disasters sites, for assisting rescue teams during the rescue operations and the list goes on. Given the capability of UAV to perform many civilian tasks to contribute to a sustainable society, this paper assesses what is needed to move the UAV to the fishing industry in order to develop the Inshore Fishing Unmanned Aerial vehicle (ISFUAV). The assessment consists of how to combine real fishing materials, their fishing material weight in relation to the ISFUAV, and the system capable of carrying those fishing materials to the fishing area into the sea and depth zone fishing.
Verification Experiment for Drone Charging Station Using RTK-GPS Verification Experiment for Drone Charging Station Using RTK-GPS $15.00

Suriyon Tansuriyong, Motoki Kyan, Kaito Numata, Shuuya Taira and Takashi Anezaki

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National Institute of Technology, Okinawa College, Japan

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Vol.3 Issue 2

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120-123

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29-12-2017

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Abstract: In recent years, Drone's research has become popular, and there is a need to automate the cycle of takeoff, flight, landing, and charging of Drone. Mainly, the problem remains in automatic battery charging. Therefore, in this research, we will realize Drone's charging station using RTK-GPS with high accuracy. We verified the landing accuracy by experiment. From the results of the verification, it was found that relative positional error between drone and the charging station can be eliminated by referring to the same reference position. Thus, the possibility of navigating Drone to the charging station can be easily implemented.
Design and Application of the Electronic Lock for Bicycle Design and Application of the Electronic Lock for Bicycle $15.00

Wenlong Han, Shenshen Cao, Yunlei Zhang, Yuxing OuYang, Xiaoqi Chen, Fengzhi Dai

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College of Electronic Information and Automation, Tianjin University of Science and Technology, China

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Volume 3 Issue 2

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70 - 73

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18-04-2017

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Abstract: A new type of the anti-theft electronic lock with the lock bolt structure is designed, which can realize the function of locking and unlocking of the bicycle safely. The hardware system includes the STC-12C5A microcontroller, RFID card, data read/write module and mechanical lock structure. The system combined the non-contact RFID card reader and the lock structure. And the static mechanical property is analyzed to meet various situations. A number of actual test results showed that the electronic lock system is safe and reliable. Keywords: Electronic lock, Lock bolt, Control center, RFID card
Hardware Detection and Parameter Tuning Method for Speed Control System of PMSM Hardware Detection and Parameter Tuning Method for Speed Control System of PMSM $15.00

Zhengqiang Song, Huiling Yang

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Yangzhou Polytechnic College, China

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Volume 2 Issue 2

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64 - 69

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10-08-2016

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Abstract: In this paper, the development of permanent magnet synchronous motor AC speed control system is taken as an example, aiming to expound the principle and parameter setting method of the system hardware, and puts forward the method of using software or hardware to eliminate the problem. Keywords: PMSM; Parameter tuning; Closed Control
Rut Detection using Lasers and In-Vehicle Stereo Camera Rut Detection using Lasers and In-Vehicle Stereo Camera $15.00

Toshiki Kage and Kousuke Matsushima

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NA

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Volume 1 Issue 1

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59 - 63

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25-12-2015

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Abstract: This paper reports a new method of detecting ruts using lasers and in-vehicle stereo camera. We process laser lines reflected in image data to obtain feature values of rut. And we determine whether it is rut or not from shapes of the laser lines. The proposed algorithm ensures processing time and cost reduction in comparison with conventional methods. Keywords: Rut detection ; Computer vision ; Inspection vehicle
Determining a Mobile Device’s Indoor and Outdoor Location considering Actual Use Determining a Mobile Device’s Indoor and Outdoor Location considering Actual Use $15.00

K.Ozaki, K.Yoshida, S.Matsuno and M.Ohyama

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NA

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Volume 1 Issue 1

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54 - 58

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25-12-2015

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Abstract: To obtain a person’s location information with high accuracy using mobile devices, it is necessary for a mobile device to switch its localization method depending on whether the user is indoors or outdoors. We propose a method to determine indoor and outdoor location using only the sensors on a mobile device. To obtain a decision with high accuracy for many devices, the method must consider individual differences between devices. We confirmed that using a majority decision method reduces the influence of individual device difference. Moreover, for highly accurate decisions in various environments, it is necessary to consider the differences in environments, such as large cities surrounded by high-rise buildings versus suburban areas. We measured classification features in different environments; the accuracy of the classifier constructed using these features was 99.6%. Keywords: GPS, Wi-Fi, Localization, Mobile Device
Localization for Autonomous Vehicle on Urban Roads Localization for Autonomous Vehicle on Urban Roads $15.00

Naoki Suganuma, Daiki Yamamoto and Keisuke Yoneda

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NA

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Volume 1 Issue 1

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47 - 53

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25-12-2015

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Abstract: Autonomous driving is an emerging technology in which a car performs recognition, decision making, and control in place of a human driver. Localization is one of the core issues for autonomous driving. In particular, driving on urban roads requires highly dependable localization techniques, because the traffic environment is more complicated than that of an expressway. In this paper, we propose a localization algorithm for an autonomous vehicle, which estimates the vehicle’s position by means of template matching. The results show that this algorithm is better suited to make estimations in various environments than the Global Navigation Satellite System and Inertial Measurement Unit (GNSS/IMU) system. Specifically, the method used in this study enables autonomous operation the vehicle up to 13km on public roads, while the GNSS/IMU system cannot achieve this. Keywords: autonomous vehicle; localization; LIDAR; infrared reflectivity; template matching
A Study of Deceleration Behavior for Cognitive Dysfunction Drivers on Public Road A Study of Deceleration Behavior for Cognitive Dysfunction Drivers on Public Road $15.00

Takahiro Yamamoto, Masaki Nakamura, Akira Urashima and Tomoji Toriyama

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NA

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Volume 1 Issue 1

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44 - 46

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25-12-2015

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Abstract: Cognitive dysfunction patients are sometimes unable to drive safely by symptoms such as executive dysfunction. We experimented with subjects equipped with wearable sensors using real cars on public roads for analyzing the driving behavior of cognitive dysfunction patients. From experimental data obtained from cognitive dysfunction patients and healthy adults (control subjects), we found there exists a difference in deceleration behaviors of cognitive dysfunction patients and healthy adults at an intersection. The result indicates that our approach may be used to evaluate cognitive dysfunction patients’ driving. Keywords: Cognitive dysfunction; Wearable Sensor; Deceleration Behavior; Driving Skill
Optimization of Rotation-Invariant Feature Detection Method for Pedestrian Recognition Optimization of Rotation-Invariant Feature Detection Method for Pedestrian Recognition $15.00

Toshiki Yahiro and Kousuke Matsushima

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NA

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Volume 1 Issue 1

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38 - 43

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25-12-2015

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Abstract: In the technology of Advanced Safety Vehicle (ASV), it is an important element to detect pedestrians by vision. However, pedestrians have pose variations such as a rotation. That’s why we cannot always get similar feature values. In order to solve this problem, we use the rotation-invariant histogram of oriented gradient (RI-HOG), but this method needs very high costs because it’s not optimized for pedestrian recognition. Therefore, we improved calculation method of RI-HOG for pedestrian recognition and compared this proposed method with the conventional method. As a result, recognition rate was increased by about 20%. Keywords: Pedestrian recognition; rotation-invariant descriptor; optimal basis functions
The proposal of unified laundry folding method and its evaluation by humans The proposal of unified laundry folding method and its evaluation by humans $15.00

Tomoya Oshima and Takashi Yoshimi

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NA

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Volume 1 Issue 1

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31 - 37

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25-12-2015

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Abstract: In this study, we propose and evaluate the unified laundry folding method for robot arm which can fold many kinds of laundries in the same way. The basic concept of this method is to make the laundry to square shape by using the developed some unified rules. The edges of the laundry are detected and the image of the laundry is enclosed in a rectangle by image processing, then the folding line to fold the protruding part inside of the laundry is defined for making the laundry square. We confirmed that the proposed unified laundry folding method can deal with T-shirt, pants and towels in the same way. And, we evaluated the proposed unified method by comparing with the human’s laundry folding method. As a result, we confirmed that our proposed unified method and the human’s folding method are similar and the proposed method will be useful for robot arm laundry folding task. Keywords: laundry folding task, image processing

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