出版者・発行元：IEEE  

DOI： 10.1109/SCIS-ISIS.2018.00220

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出版者・発行元：IEEE  

DOI： 10.1109/SMC.2018.00149

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出版者・発行元：IEEE  

DOI： 10.1109/SMC.2018.00151

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出版者・発行元：IEEE  

DOI： 10.23919/WAC.2018.8430398

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出版者・発行元：Springer  

DOI： 10.1007/978-3-319-97586-3_35

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出版者・発行元：IEEE  

DOI： 10.1109/MHS.2018.8887062

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出版者・発行元：IEEE  

DOI： 10.1109/SCIS-ISIS.2018.00219

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出版者・発行元：IEEE  

DOI： 10.1109/MHS.2017.8305188

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Fuji Technology Press  

RANdom SAmple Consensus (RANSAC) has been applied to many 3D image processing problems such as homography matrix estimation problems and shape detection from 3D point clouds, and is one of the most popular robust estimator methods. However, RANSAC has a problem related to the trade-off between computational cost and stability of search because RANSAC is based on random sampling. Genetic Algorithm SAmple Consensus (GASAC) based on a population-based multi-point search was proposed in order to improve RANSAC. GASAC can im-prove the performance of search. However, it is sometimes difficult to maintain the genetic diversity in the search if the large size of outliers is included in a data set. Furthermore, a computational time of GASAC sometimes is slower than that of RANSAC because of calculation of the genetic operators. This paper proposes Evolution Strategy SAmple Consensus (ESSAC) as a new robust estimator. ESSAC is based 011 Evolution Strategy in order to maintain the genetic diversity. In ESSAC, we apply two heuristic searches to ESSAC. One is a search range control, the other is adaptive/self-adaptive mutation. By applying these heuristic searches, the trade-off between computational speed and search stability can be improved. Finally, this paper shows several experimental results in order to evaluate the effectiveness of the proposed method.

DOI： 10.20965/jaciii.2016.p0788

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：ELSEVIER SCIENCE BV  

In this paper, a new network is proposed for automated recognition and classification of the environment information into regions, or nodes. Information is utilized in learning the topological map of an environment. The architecture is based upon a multi-channel Adaptive Resonance Associative Memory (ARAM) that comprises of two layers, input and memory. The input layer is formed using the Multiple Bayesian Adaptive Resonance Theory, which collects sensory data and incrementally clusters the obtained information into a set of nodes. In the memory layer, the clustered information is used as a topological map, where nodes are connected with edges. Nodes in the topological map represent regions of the environment and stores the robot location, while edges connect nodes and stores the robot orientation or direction. The proposed method, a Multi-channel Bayesian Adaptive Resonance Associative Memory (MBARAM) is validated using a number of benchmark datasets. Experimental results indicate that MBARAM is capable of generating topological map online and the map can be used for localization. (C) 2015 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.asoc.2015.09.031

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：SPRINGER INT PUBLISHING AG  

This paper proposes a 3D point cloud segmentation method using a reflection intensity of Laser Range Finder (LRF). In this paper, we use LRF and tilt unit for acquiring a 3D point cloud. First of all, we apply Growing Neural Gas (GNG) to the point cloud for learning a topological structure of the point cloud. Next, we proposed a segmentation method based on an intensity histogram that is composed of the nearest data of each node. Finally, we show experimental results of the proposed method and discuss the effectiveness of the proposed method.

DOI： 10.1007/978-3-319-43518-3_33

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

DOI： 10.1109/IROS.2016.7759654

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

This paper proposes a real-time feature extraction and segmentation method for a 3D point cloud. First of all, we apply Growing Neural Gas with Utility (GNG-U) to the point cloud for learning a topological structure. However, the standard GNG-U cannot learn the topological structure of 3D space environment and color information simultaneously. To this end, we then modify the GNG-U algorithm by using a weight vector. we propose a surface feature extraction and segmentation method by efficiently utilizing the topological structure. Our segmentation method is based on a region growing method whose similarity value uses the inner value of two normal vectors connected by the topological structure. We show experimental results of the proposed method and discuss the effectiveness of the proposed method.

DOI： 10.1109/HSI.2016.7529667

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：Springer  

DOI： 10.1007/978-3-319-22873-0_6

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

This paper presents a new framework for mobile robot to perform localization and build topological-metric hybrid map simultaneously. The proposed framework termed as Genetic Bayesian ARAM consists of two main components: 1) Steady state genetic algorithm (SSGA) for self-localization and occupancy grid map building and 2) Bayesian Adaptive Resonance Associative Memory (ARAM) for topological map building. The proposed method is validated using a mobile robot. Result show that Genetic Bayesian ARAM capable of generate hybrid map online and perform localization simultaneously.

DOI： 10.1109/SSCI.2015.48

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

Recently, robust estimators are expected in various fields such as signal processing and machine learning. In our previous work, we proposed Evolution Strategy Sample Consensus (ESSAC) as a new robust estimator method and improved a trade off between a calculation time and stability of SAmple Consensus (SAC) algorithms. In this paper, we show several experiments for behavior analysis of ESSAC in order to discuss why ESSAC enable to search stably in the dataset including the huge number of noises. and analyze several experiments related with the fitness function of SAC and the behavior of ESSAC.

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

This paper proposes a localization method using multiresolution maps for the navigation of multiple mobile robots based on formation behaviors. The remote control of multiple mobile robots is one the most important tasks in robotics to realize distributed remote monitoring in unknown and/or dynamic environments. However, it is very difficult for a human operator to control multiple mobile robots separately at the same time. Therefore, autonomous formation behaviors of multiple robots are required to reduce mental and physical loads of the human operator. If each mobile robot can estimate the self-position or relative position in a group, it is easier for multiple mobile robots to realize formation behaviors. First, we propose a method of simultaneous localization and mapping based on a grid approach. Next, we explain how to share the build map among multiple mobile robots, and propose a self-localization method based on multiresolution maps. Furthermore, we explain the formation behaviors of multiple mobile robots. Finally, we show several experimental results, and discuss the effectiveness of the proposed method.

DOI： 10.1109/TII.2013.2261306

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

This paper proposes a method of constituting the formation of a multi-robot system for exploration and monitoring. First, we apply a method of multi-objective behavior coordination for integrating behavior outputs from the fuzzy control for collision avoidance and target tracing. Second, we apply a spring model to calculate the temporary target position of each robot for the formation behavior. Third, we constitute monitoring formation, which is realized by enclosing behavior of multi-robot. Finally, we discuss the effectiveness of the proposed method through several simulation results.

DOI： 10.1109/RVSP.2013.24

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

This paper proposes a localization method using shared information for teleoperation of multiple robots based on formation behaviors. The localization is one of the most important capabilities. However, other robots can be considered as unknown objects when a mobile robot performs initial self-localization. It is difficult to estimate the initial position if the other robots enter the sensing range of the mobile robot. However, the robot can perform the initial self-localization more efficiently by sharing the map information and each self-position. Therefore, we propose a method of effective initial self-localization using the position information of the other mobile robots and the subtracted measurement data of LRF for multi-robot systems. Finally, we show several experimental results, and discuss the effectiveness of the proposed method.

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：International Federation of Automatic Control  

This paper proposes a method of attention allocation for multi-modal perception of humanfriendly robot partners based on various types of sensors built in a smart phone. First, we propose human and object detection method using octagonal templates based on evolutionary robot vision. Next, we propose an integration method for estimating human behaviors based on the human detection using color image by the multi-layered spiking neural network using the time series of positions of human and object. Furthermore, we propose a method of attention allocation based on the time series of human behavior recognition. Finally, we show several experimental results of the proposed method, and discuss the future direction on this research. Copyright © 2013 IFAC.

DOI： 10.3182/20130811-5-US-2037.00054

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

This paper proposes a method of feature extraction from 3D point clouds for informationally structured space including sensor networks and robot partners for co-existing with people. The informationally structured space realizes the quick update and access of valuable and useful information for both people and robots on real and virtual environments. Our method is based on Hierarchical Growing Neural Gas (HGNG). This method is one of self-organizing neural network based on unsupervised learning First, we propose 3D map building method using Kinect in order to acquire the 3D point clouds. Next, we propose the method of the feature extracting method based on HGNG. Finally, we show experimental results of the proposed method and discuss the effectiveness of the proposed method.

DOI： 10.1109/IJCNN.2013.6706825

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

This paper proposes a multimodal communication method for human-friendly robot partners based on various types of sensors. First, we explain informationally structured space to extend the cognitive capabilities of robot partners based on environmental systems. Next, we discuss the suitable measurement range for recognition technologies of touch interface, voice recognition, human detection, gesture recognition, and others. Based on the suitable measurement ranges, we propose an integration method to estimate human behaviors based on the human detection using color image and 3-D distance information, and gesture recognition by the multilayered spiking neural network using the time series of human-hand positions. Furthermore, we propose a conversation system to realize the multimodal communication with a person. Finally, we show several experimental results of the proposed method, and discuss the future direction of this research.

DOI： 10.1109/TSMCC.2012.2213810

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Springer Tokyo  

The paper deals with simultaneous optimization of path planning of mobile robots and flow shop scheduling problem. The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. The objective is to minimize the path length without colliding with an obstacle. On the other hand, shop scheduling problems deal with processing a given set of jobs on a given number of machines. Each operation has an associated machine on which it has to be processed for a given length of time. The problem is to minimize the overall time demand of the whole process. In this paper, we deal with two robots carrying items between the machines. Bacterial memetic algorithm is proposed for solving this combined problem. The algorithm is verified by experimental simulations and compared to classical techniques.

DOI： 10.1007/s10015-012-0021-9

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：SPRINGER HEIDELBERG  

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. This problem belongs to the group of combinatorial optimization problems which are approached by modern optimization techniques such as evolutionary algorithms. In this paper the bacterial memetic algorithm is proposed for path planning of a mobile robot. The objective is to minimize the path length and the number of turns without colliding with an obstacle. The representation used in the paper fits well to the algorithm. Memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. One advantage of these operators is that they easily can handle individuals with different length. The method is able to generate a collision-free path for the robot even in complicated search spaces. The proposed algorithm is tested in real environment.

DOI： 10.1007/s12293-012-0076-0

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：Springer  

The localization is one of the most important capabilities for mobile robots. However, other robots can be considered as unknown objects when a mobile robot performs localization, because other robots can enter the sensing range of a mobile robot. Therefore, we propose a method of intelligent selflocalization using evolutionary computation for multiple mobile robots based on simultaneous localization and mapping (SLAM). First, we explain the method of SLAM using occupancy grid mapping by a single mobile robot. Next, we propose an intelligent self-localization method using multi-resolution map and evolutionary computation based on relative position of other robots in the sensing range. The experimental results show the effectiveness of the proposed method. © Springer-Verlag Berlin Heidelberg 2012.

DOI： 10.1007/978-3-642-33509-9_22

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記述言語：英語   掲載種別：研究論文（学術雑誌）  

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. In case of probabilistic environment not only static obstacles obstruct the free passage of the robot, but there are appearances of obstacles with probability. The problem is approached by the bacterial memetic algorithm. The objective is to minimize the path length and the number of turns without colliding with an obstacle. Our method is able to generate a collision-free path in probabilistic environment. The proposed algorithm is tested by simulations. © Springer-Verlag Berlin Heidelberg 2012.

DOI： 10.1007/978-3-642-29934-6_42

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

Recently, tele-operation using multi-robot system has been discussed from various viewpoints of shared autonomy, intelligent control, formation behaviors, and information visualization. Furthermore, tele-operation systems have been applied to the remote monitoring of dangerous areas for people such as deep seas, nuclear power plants, and disaster-stricken areas. In this paper, we focus on the structured intelligence based on interconnected intelligent functions of map building, localization of mobile robots, 3D reconstruction and visualization, and human-friendly interface for tele-operation. © 2011 IEEE.

DOI： 10.1109/MHS.2011.6102177

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：ALIFE ROBOTICS CO, LTD  

The paper deals with simultaneous optimization of path planning of mobile robots and flow shop scheduling problem. The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. The objective is to minimize the path length without colliding with an obstacle. On the other hand, shop scheduling problems deal with processing a given set of jobs on a given number of machines. Each operation has an associated machine on which it has to be processed for a given length of time. The problem is to minimize the makespan, i.e., the overall time demand of the whole process. In this paper we deal with two robots carrying items between the machines. Bacterial memetic algorithm is proposed for solving the problem.

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IOS PRESS  

Recently, multiple mobile robots have been used for exploration and remote monitoring in unknown areas. The required functions for human-friendly remote monitoring and control are (1) Extraction of human intention, (2) Semi-autonomous tele-operation, (3) Multi-robot formation behaviors, (4) Sensor fusion for information extraction, (5) Perception of situation, (6) Decision support based on information visualization and (7) Extraction of human interest. We proposed an intelligent navigation system for human-friendly remote monitoring and control. The intelligent navigation system for multiple mobile robots is composed of simultaneous localization and mapping (SLAM), intelligent path planning based on multi-resolution map, 3D information visualization system, and human navigation system based on touch interface. In this chapter, we focus on the information visualization and map building for remote monitoring and control of multiple mobile robots, and show several experimental results of the proposed methods.

DOI： 10.3233/978-1-61499-092-5-120

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）  

This paper discusses the multi-modal communication for robot partners based on computational intelligence in informationally structured space. First, we explain recognition methods of touch interface, voice recognition, human detection, gesture recognition used in the multi-modal communication. Furthermore, we propose a conversation system to realize the multi-modal communication with a person. Finally, we show several experimental results of the proposed method, and discuss the future direction on this research. © 2012 IEEE.

DOI： 10.1109/GCCE.2012.6379611

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

This paper proposes a method for 3D modeling of environments used to perform teleoperation of a mobile robot. Recently, the expectation to tele-operated mobile robots has been increasing much in order to perform a monitoring in various scenes. However, there are many critical problems in teleoperated systems. Especially, we must expand visual range from a robot, the usability of human interface, and intention sharing between the robot and operator. First, we discuss information visualization for human-friendly tele-operation. Next, we propose a tele-operating system based on multi-resolution map. Finally, we propose a method of 3D modeling using Microsoft Kinect sensor, and show several experimental results of the proposed method.

DOI： 10.1109/CEC.2012.6253007

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

This paper proposes a method for constituting the formation of a multi-robot system according to dynamically changing environments. First, we apply a method of multi-objective behavior coordination for integrating behavior outputs from the fuzzy control for collision avoidance and target tracing. Second, we apply a spring model to calculate the temporary target position of each robot for the formation behavior. Third, we discuss multi-robot behaviors based on the concept of coupling. The tight coupling is realized by the spring model while the loose coupling is realized by the individual decision making based on connection and disconnection with other robots. Furthermore, the proposed method is applied to the exploration in unknown environments. Finally, we discuss the effectiveness of the proposed method through several simulation results.

DOI： 10.1109/FUZZ-IEEE.2012.6251150

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

Simultaneous localization and mapping (SLAM) is one of important topics in robotics. However, we must consider various intelligent behaviors in SLAM, e.g., the exploration of unknown areas and effective path planning of mobile robots. To realize these intelligent behaviors, we use a multi-resolution map. The multi-resolution map can be updated by the operators suitable to a specific aim. The first aim is to represent the occupied or empty cells in the built map. The next aim is to represent the unknown areas in the built map. These are used for the intelligent planning. The intelligent planning is composed of preplanning, online planning, and adaptive planning. These planning methods are used according to the state of a built map. The experimental results show the effectiveness of the proposed method. © 2011 IEEE.

DOI： 10.1109/RIISS.2011.5945794

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

This paper discusses measurement methods of human behaviors based on sensor network and human interaction of rehabilitation using robot partners. First, we explain robot partners and sensor networks for rehabilitation. Next, we apply a steady-state genetic algorithm to extract human motions from 3D distance image. Finally, we discuss the effectiveness of the proposed methods through several experimental results.

DOI： 10.1109/FUZZY.2011.6007712

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

Recently, the expectation to tele-operated mobile robots has been increasing much in order to perform the monitoring in various scenes. However, there are many critical problems in tele-operated system. Especially, we must improve the restriction of visual range, the usability of human interface, and intention sharing with the operator. In this paper, we discuss the monitoring system of a tele-operated robot and human interface based on visual information and distance information from the tele-operated mobile robots. Next, we propose a method of a navigation system based on multi-featured visualization. Finally, we propose a tele-operated system using iPhone, and show several experimental results of the proposed method. © 2011 IEEE.

DOI： 10.1109/RIISS.2011.5945796

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. This problem belongs to the group of hard optimization problems which can be approached by modern optimization techniques such as evolutionary algorithms. In this paper the bacterial memetic algorithm is proposed for path planning of a mobile robot. The representation used in the paper fits well to the algorithm. Memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. One advantage of these operators is that they easily can handle individuals with different length. The proposed algorithm is tested in real environment. © 2011 IEEE.

DOI： 10.1109/RIISS.2011.5945787

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：IEEE  

Recently, multi-robot systems have been discussed to realize a large size of distributed autonomous system. Furthermore, multi-robot systems have been applied to various problems such as autonomous guided vehicles, soccer robots, and search and rescue system by multi-robot. This paper proposes intelligent formation behavior for the multi-robot based on sensor fusion. First, we discuss multi-agent systems and wireless network technologies. Next, we explain the hardware specification of robot and tele-operated system and wireless communication. Finally, we show experimental results, and discuss the availability of intelligent formation behavior for multi-robot.

DOI： 10.1109/FUZZY.2011.6007709

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