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Doshisha University, Japan

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10 Papers

Moving-object Tracking with Lidar Mounted on Two-wheeled Vehicle

Topics: Image Processing; Intelligent Transportation Technologies and Systems; Mechatronics Systems; Perception and Awareness; Sensors Fusion

Authors: Shotaro Muro ¹ , Yohei Matsui ¹ , Masafumi Hashimoto ² and Kazuhiko Takahashi ²

Affiliations: ¹ Graduate School of Doshisha University, Kyotanabe, Kyoto 6100321 and Japan , ² Faculty of Science and Engineering, Doshisha University, Kyotanabe, Kyoto 6100321 and Japan

Digital Object Identifier: 10.5220/0007948304530459

Proceedings of ICINCO 2019, ISBN: 978-989-758-380-3

Quick Abstract

This paper presents a tracking (estimating position, velocity and size) of moving objects, such as cars, two-wheeled vehicles, and pedestrians, using a multilayer lidar mounted on a two-wheeled vehicle. The vehicle obtains its own pose (position and attitude angle) by on-board global navigation satellite system/inertial navigation system (GNSS/INS) unit and corrects the distortion in the lidar-scan data by interpolating the pose information. The corrected lidar-scan data is mapped onto 3D voxel map represented in the world coordinate frame. Subsequently, the vehicle extracts the interested lidar-scan data from the current lidar-scan data using the normal distributions transform (NDT) scan matching based map-subtraction method. The extracted scan data are mapped onto an elevation map, and moving objects are detected based on an occupancy grid method. Finally, detected moving objects are tracked based on the Bayesian Filter. Experimental results show the performance of the proposed method.

Related Ontology Subjects/Areas/Topics (8)

Image Processing	Mechatronics Systems	Sensors Fusion
Informatics in Control, Automation and Robotics	Perception and Awareness	Signal Processing, Sensors, Systems Modeling and Control
Intelligent Transportation Technologies and Systems	Robotics and Automation

Point-cloud Mapping using Lidar Mounted on Two-wheeled Vehicle based on NDT Scan Matching

Topics: Image Processing; Vision, Recognition and Reconstruction; Intelligent Transportation Technologies and Systems; Sensors Fusion

Authors: Kohei Tokorodani ¹ , Masafumi Hashimoto ² , Yusuke Aihara ¹ and Kazuhiko Takahashi ²

Affiliations: ¹ Graduate School of Doshisha University, Kyotanabe, Kyoto 6100321 and Japan , ² Faculty of Science and Engineering, Doshisha University, Kyotanabe, Kyoto 6100321 and Japan

Digital Object Identifier: 10.5220/0007946204460452

Proceedings of ICINCO 2019, ISBN: 978-989-758-380-3

Quick Abstract

This paper presents a method for generating a 3D point-cloud map using multilayer lidar mounted on two-wheeled vehicle. The vehicle identifies its own 3D pose (position and attitude angle) in a lidar-scan period using the normal distributions transform (NDT) scan-matching method. The vehicle’s pose is updated in a period shorter than the lidar-scan period using its attitude angle and angular velocity measured by an inertial measurement unit (IMU). The pose estimation is based on the extended Kalman filter (EKF) under the assumption that the vehicle moves at nearly constant translational and angular velocities. The vehicle’s pose is further estimated in a period shorter than measurement period of the IMU using a linear interpolation method. The estimated poses of the vehicle are applied to distortion correction of lidar-scan data, and a point-cloud map is generated based on the corrected lidar-scan data. Experimental results of mapping a road environment using a 32-layer lidar mounted on a bicycle show the efficancy of the proposed method in comparison with conventional methods of distortion correction of lidar-scan data.

Related Ontology Subjects/Areas/Topics (7)

Image Processing	Robotics and Automation	Signal Processing, Sensors, Systems Modeling and Control
Informatics in Control, Automation and Robotics	Sensors Fusion	Vision, Recognition and Reconstruction
Intelligent Transportation Technologies and Systems

Distortion Correction of Laser Scan Data from In-vehicle Laser Scanner based on Kalman Filter and NDT Scan Matching

Topics: Image Processing; Mobile Robots and Autonomous Systems

Authors: Kimiaki Inui ¹ , Masahide Morikawa ¹ , Masafumi Hashimoto ² and Kazuhiko Takahashi ²

Affiliations: ¹ Graduate School of Doshisha University, Japan , ² Doshisha University, Japan

Digital Object Identifier: 10.5220/0006422303290334

Proceedings of ICINCO 2017, ISBN: 978-989-758-264-6

Quick Abstract

This paper presents a Kalman-filter-based method of correcting distortion in 3D laser-scan data from in-vehicle multilayer laser scanner. A robot identifies its own 3D pose (position and attitude) in a laser-scan period using the normal-distributions transform (NDT) scan-matching method. Based on the pose information, the robot’s pose is predicted and smoothed in a period shorter than the scan period using Kalman filter under the assumption that the robot moves at nearly constant linear and turning velocities. The predicted and smoothed poses of the robot are applied to map laser-scan data onto a world coordinate frame. Subsequently, the robot again identifies its own 3D pose from the mapped scan data using NDT scan matching. This iterative process enables the robot to correct the distortion of laser-scan data and accurately map the laser-scan data onto the world coordinate frame. Experimental results of mapping a signal light in a road environment validate the proposed method.

Related Ontology Subjects/Areas/Topics (4)

Image Processing		Mobile Robots and Autonomous Systems		Robotics and Automation
Informatics in Control, Automation and Robotics

Comparison of Power Consumption Reduce Effect of Intelligent Lighting System and Lighting Control System Using Motion Sensors

Topics: Ambient Intelligence; Autonomous Systems

Authors: Katsunori Onobayashi ¹ , Yuki Sakakibara ¹ , Hiromitsu Nakabayashi ¹ , Mitsunori Miki ² and Hiroto Aida ²

Affiliations: ¹ Doshisha University, Japan , ² Doshishsa University, Japan

Digital Object Identifier: 10.5220/0005191403340340

Proceedings of ICAART 2015, ISBN: 978-989-758-074-1

Quick Abstract

Designed in accordance with conventional uniform lighting systems, lighting control systems that use motion sensors allow lighting control per area because they only switch on the lights linked to the motion sensors. However, further power consumption reductions can be possible using a dimmer control for individual lights to supply the level of brightness desired by each worker (hereafter referred to as target illuminance) instead of the per-area method. In the present study, we therefore conducted a comparative experiment with regard to the power consumption of a lighting control system that uses motion sensors and a system that controls the lighting for each worker (hereafter referred to as intelligent lighting system). The validity of the power consumption reduction in offices where intelligent lighting system was introduced was determined using a comparative simulation. A simulation was performed for various worker patterns in a mock-up of an actual office environment to verify the validity of the proposed system. The simulation results showed the effectiveness of the proposed method under all work patterns and thus indicated that the intelligent lighting system saves more energy than the lighting control system that uses motion sensors.

Related Ontology Subjects/Areas/Topics (5)

Agents		Artificial Intelligence		Symbolic Systems
Ambient Intelligence		Autonomous Systems

Dynamic Analysis for Golf Swing using of Mode Synthetics Method for Suggesting an Optimal Club

Topics: Sports Biomechanics; Simulation and Mathematical Modeling

Authors: Kenta Matsumoto ¹ , Nobutaka Tsujiuchi ² , Takayuki Koizumi ² , Akihito Ito ² , Masahiko Ueda ³ and Kosuke Okazaki ³

Affiliations: ¹ Doshisha University, Japan , ² Doshisha Univerisity, Japan , ³ Sumitomo Rubber Industries andLtd, Japan

Digital Object Identifier: 10.5220/0005070700270033

Proceedings of icSPORTS 2014, ISBN: 978-989-758-057-4

Quick Abstract

Advance of measurement system permits the measurement of high accuracy data. This study proposes analysis of shaft movement using this system. Firstly, we made a shaft model using finite element method and a club head model as concentrated mass. Secondly, we reduced amount of calculation by applying mode synthetics method. Input data for simulation is inertia force and torque calculated from swing data that is measured by motion capturing system and is treated data manually. Finally, we simulated shaft movement using these data, we cloud repeat shaft movement of face direction and toe direction.

Related Ontology Subjects/Areas/Topics (5)

Computer Systems in Sports		Simulation and Mathematical Modeling		Sports Biomechanics
Signal Processing and Motor Behavior		Sport Science Research and Technology

Laser-based Tracking of People and Vehicles by Multiple Mobile Robots

Topics: Intelligent Transportation Technologies and Systems; Mobile Robots and Autonomous Systems; Perception and Awareness; Sensors Fusion

Authors: Masafumi Hashimoto ¹ , Ryunosuke Izumi ² , Yuto Tamura ² and Kazuhiko Takahashi ¹

Affiliations: ¹ Doshisha University, Japan , ² Graduate School of Doshisha University, Japan

Digital Object Identifier: 10.5220/0005084205220527

Proceedings of ICINCO 2014, ISBN: 978-989-758-040-6

Quick Abstract

This paper presents laser-based tracking of moving objects conducted by a group of mobile robots located near one another. Each robot finds moving objects such as people, cars, and bicycles in its own laser-scanned images using a binarized occupancy-grid-based method. It then sends laser measurements related to the detected moving objects to a central server. The central server estimates the pose and size of the moving objects via the Kalman filter based on received measurements; it then feeds that information back to the robots. Rule-based and global-nearest-neighbor-based data associations are applied for matching of tracked objects and laser measurements in multitarget environments. In this cooperative tracking method, the central server collects the laser measurements from all robots; hence, the robots can always track invisible or partially invisible objects. The experimental results for two robots in an outdoor environment validate our tracking method.

Related Ontology Subjects/Areas/Topics (7)

Informatics in Control, Automation and Robotics	Perception and Awareness	Sensors Fusion
Intelligent Transportation Technologies and Systems	Robotics and Automation	Signal Processing, Sensors, Systems Modeling and Control
Mobile Robots and Autonomous Systems

Remarks on an Adaptive-type Self-tuning Controller using Quantum Neural Network with Qubit Neurons

Topics: Machine Learning in Control Applications; Soft Computing; Neural Networks Based Control Systems; Engineering Applications

Authors: Kazuhiko Takahashi , Yuka Shiotani and Masafumi Hashimoto

Affiliation: Doshisha University, Japan

Digital Object Identifier: 10.5220/0004425701070112

Proceedings of ICINCO 2013, ISBN: 978-989-8565-70-9

Quick Abstract

This paper presents a self-tuning controller based on a quantum neural network and investigates the controller’s characteristics for control systems. A multi-layer quantum neural network which uses qubit neurons as an information processing unit is utilized to design an adaptive-type self-tuning controller which conducts the training of the quantum neural network as an online process. As an example of designing the self-tuning controller, either a proportional integral derivative controller or a fuzzy logic controller is utilized as a conventional controller for which parameters are tuned by the quantum neural network. To evaluate the learning performance and capability of the adaptive-type quantum neural self-tuning controller, we conduct computational experiments to control the single-input single-output non-linear discrete time plant. The results of the computational experiments confirm both feasibility and effectiveness of the proposed self-tuning controller.

Related Ontology Subjects/Areas/Topics (12)

Artificial Intelligence	Enterprise Information Systems	Neural Networks Based Control Systems
Artificial Intelligence and Decision Support Systems	Informatics in Control, Automation and Robotics	Robotics and Automation
Computational Intelligence	Intelligent Control Systems and Optimization	Signal Processing, Sensors, Systems Modeling and Control
Engineering Applications	Machine Learning in Control Applications	Soft Computing

A REFINING METHOD OF OBTAINED ATTRIBUTES TO CHARACTERIZE UNDEFINED CONCEPTS USING SEARCH ENGINE

Authors: Noriyuki Okumura ¹ and Yuto Hatakoshi ²

Affiliations: ¹ Nagano National College of Technology, Japan , ² Doshisha University, Japan

Digital Object Identifier: 10.5220/0003697804930497

Proceedings of SSW 2011/IC3K, ISBN: 978-989-8425-80-5

Quick Abstract

In this paper, we propose a method to resolve problems of the attributes obtaining method using WWW search engine characterizing undefined concepts, which do not exist in Concept-base. Concept-base is an key database constituting Word Association Mechanism to perform commonsense judgment. Concept-base was constructed automatically by electronic dictionaries and newspapers. Therefore Concept-base has about 120,000 statically defined concepts. Nevertheless, it has no effective learning system. This paper proposes a method to make Concept-base to learn concepts dynamically using Auto Feedback system. In addition, a removal method of noise at-tributes is also proposed. We present attributes refinement method that paid attention to changing with time of the Internet. Furthermore, we inspect the effectiveness by an evaluation experiment.

REALIZATION OF EFFECTIVE DISASTER VICTIM SUPPORT THROUGH INFORMATION INTEGRATION AND VISUALIZATION USING GIS

Topics: Expert Systems in Healthcare; Practice Based Research Methods for Assistive Technology; Design and Development Methodologies for Healthcare IT; Healthcare Management Systems

Authors: Munenari Inoguchi ¹ , Keiko Tamura ¹ , Shigeo Tatsuki ² and Haruo Hayashi ³

Affiliations: ¹ Niigata University, Japan , ² Doshisha University, Japan , ³ Kyoto University, Japan

Digital Object Identifier: 10.5220/0002693703810387

Proceedings of HEALTHINF 2010/BIOSTEC, ISBN: 978-989-674-016-0

Quick Abstract

Disaster victims, who cannot make progress in their life recovery by themselves, need to be supported generously by local government. However, there is no information management system for the progress of their life recovery process in order to identify the individual needs of victims. In the first step of this research, we designed and developed Victims Master Database which stored the situation of progress of victims’ life recovery process. This master database is developed by the integration of 5 databases; two of those are Residents’ Ledger and Fixed Asset Tax Rolls which are used in daily routine business, and the others are databases for granted certification of building damage degree, relief programs management and public temporary housing management which are constructed after the disaster. In this integration, however, it is unable to connect together simply because there is no relational key in each database. Against this issue, we applied GeoWrap method which can connect databases in GIS by the spatial proximity between pieces of information. In the second step, we developed the information management system which can ascertain victims’ life recovery status and visualize it in spatial. By using this system, responders developed common operational pictures of victims’ status, and provide generous support for victims with special needs effectively.

Related Ontology Subjects/Areas/Topics (10)

Artificial Intelligence	Health Information Systems	Knowledge-Based Systems
Biomedical Engineering	Healthcare Management Systems	Practice Based Research Methods for Assistive Technology
Design and Development Methodologies for Healthcare IT	Knowledge Engineering and Ontology Development	Symbolic Systems
Expert Systems

EFFECTIVENESS OF AVATARS FOR SUBJECTIVE ANNOTATION

Topic: Multimedia and User Interfaces

Authors: Fuyuko Ito ¹ , Yasunari Sasaki ² , Tomoyuki Hiroyasu ² and Mitsunori Miki ²

Affiliations: ¹ Graduate School of Engineering, Doshisha University, Japan , ² Doshisha University, Japan

Digital Object Identifier: 10.5220/0001524700740081

Proceedings of WEBIST 2008, ISBN: 978-989-8111-27-2

Quick Abstract

Consumer Generated Media (CGM) is growing rapidly and the amount of content is increasing. However, it is often difficult for users to extract important contents and the existence of contents recording their experiences can easily be forgotten. As there are no methods or systems to indicate the subjective value of the contents or ways to reuse them, subjective annotation appending subjectivity, such as feelings and intentions, to contents is needed. Representation of subjectivity depends on not only verbal expression, but also nonverbal expression. Linguistically expressed annotation, typified by collaborative tagging in social bookmarking systems, has come into widespread use, but there is no system of nonverbally expressed annotation on the web. We proposed the use of controllable avatars as a means of nonverbal expression of subjectivity, and confirmed the consistency of feelings elicited by avatars over time for an individual and in a group. In addition, we compared the expressiveness and ease of subjective annotation between collaborative tagging and controllable avatars. The result indicated that the feelings evoked by avatars are consistent in both cases, and using controllable avatars is easier than collaborative tagging for representing feelings elicited by contents that do not express meaning, such as photos.

Related Ontology Subjects/Areas/Topics (3)

Multimedia and User Interfaces

Web Information Systems and Technologies

Web Interfaces and Applications

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