Naoyuki Kubota

7202158579

Publications - 16

Human-Centric Automation and Optimization for Smart Homes

J. Botzheim Noel Nuo Wi Tay Naoyuki Kubota

Publication Name: IEEE Transactions on Automation Science and Engineering

Publication Date: 2018-10-01

Volume: 15

Issue: 4

Page Range: 1759-1771

Description:

A smart home needs to be human-centric, where it tries to fulfill human needs given the devices it has. Various works are developed to provide homes with reasoning and planning capability to fulfill goals, but most do not support complex sequence of plans or require significant manual effort in devising subplans. This is further aggravated by the need to optimize conflicting personal goals. A solution is to solve the planning problem represented as constraint satisfaction problem (CSP). But CSP uses hard constraints and, thus, cannot handle optimization and partial goal fulfillment efficiently. This paper aims to extend this approach to weighted CSP. Knowledge representation to help in generating planning rules is also proposed, as well as methods to improve performances. Case studies show that the system can provide intelligent and complex plans from activities generated from semantic annotations of the devices, as well as optimization to maximize personal constraints' fulfillment. Note to Practitioners - Smart home should maximize the fulfillment of personal goals that are often conflicting. For example, it should try to fulfill as much as possible the requests made by both the mother and daughter who wants to watch TV but both having different channel preferences. That said, every person has a set of goals or constraints that they hope the smart home can fulfill. Therefore, human-centric system that automates the loosely coupled devices of the smart home to optimize the goals or constraints of individuals in the home is developed. Automated planning is done using converted services extracted from devices, where conversion is done using existing tools and concepts from Web technologies. Weighted constraint satisfaction that provides the declarative approach to cover large problem domain to realize the automated planner with optimization capability is proposed. Details to speed up planning through search space reduction are also given. Real-time case studies are run in a prototype smart home to demonstrate its applicability and intelligence, where every planning is performed under a maximum of 10 s. The vision of this paper is to be able to implement such system in a community, where devices everywhere can cooperate to ensure the well-being of the community.

Open Access: Yes

DOI: 10.1109/TASE.2018.2789658

Practical robot edutainment activities program for junior high school students

J. Botzheim Takuya Hashimoto Noriko Takase Naoyuki Takesue Naoyuki Kubota

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2016-01-01

Volume: 9834 LNCS

Issue: Unknown

Page Range: 111-121

Description:

In this paper, we describe the approach of the research activities in order to take advantage of the creativity and thinking abilities in practical research of the robot for junior high school female students. The students mainly understand the main idea and the definition of robots and they created them based on information and advice provided by our university and teachers. As a result, the students created the robots by their unique imagination.

Open Access: Yes

DOI: 10.1007/978-3-319-43506-0_10

Evolving spiking neural network for robot locomotion generation

J. Botzheim Noriko Takase Naoyuki Kubota

Publication Name: 2015 IEEE Congress on Evolutionary Computation CEC 2015 Proceedings

Publication Date: 2015-09-10

Volume: Unknown

Issue: Unknown

Page Range: 558-565

Description:

In this paper, we propose locomotion generation for a mobile robot. Legged robot can walk in various complex terrains such as stairs as well as in flat environment. However, setting its behaviour to adapt to various environments in advance is very difficult. The robot can mimic the movement of organisms based on computational intelligence. In this study, we apply spiking neural network, which can take into account the transition of temporal information between the neurons. More specifically, the motion patterns are generated by applying a spiking neural network trained by Hebbian learning and evolution strategy, by using data provided by the physics engine measuring the distance walked by the robot and applied the motion patterns to real robot. Simulation was conducted to confirm the proposed technique.

Open Access: Yes

DOI: 10.1109/CEC.2015.7256939

A novel multimodal communication framework using robot partner for aging population

J. Botzheim Dalai Tang Bakhtiar Yusuf Chee Seng Chan Naoyuki Kubota

Publication Name: Expert Systems with Applications

Publication Date: 2015-06-01

Volume: 42

Issue: 9

Page Range: 4540-4555

Description:

In developed country such as Japan, aging has become a serious issue, as there is a disproportionate increasing of elderly population who are no longer able to look after themselves. In order to tackle this issue, we introduce human-friendly robot partner to support the elderly people in their daily life. However, to realize this, it is essential for the robot partner to be able to have a natural communication with the human. This paper proposes a new communication framework between the human and robot partner based on relevance theory as the basis knowledge. The relevance theory is implemented to build mutual cognitive environment between the human and the robot partner, namely as the informationally structured space (ISS). Inside the ISS, robot partner employs both verbal as well as non-verbal communication to understand human. For the verbal communication, Rasmussen's behavior model is implemented as the basis for the conversational system. While for the non-verbal communication, environmental and human state data along with gesture recognition are utilized. These data are used as the perceptual input to compute the robot partner's emotion. Experimental results have shown the effectiveness of our proposed communication framework in establishing natural communication between the human and the robot partner.

Open Access: Yes

DOI: 10.1016/j.eswa.2015.01.016

Spiking neural network based emotional model for robot partner

J. Botzheim Naoyuki Kubota

Publication Name: IEEE Ssci 2014 2014 IEEE Symposium Series on Computational Intelligence Riiss 2014 2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space Proceedings

Publication Date: 2015-01-13

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper, a spiking neural network based emotional model is proposed for a smart phone based robot partner. Since smart phone has limited computational power compared to personal computers, a simple spike response model is applied for the neurons in the neural network. The network has three layers following the concept of emotion, feeling, and mood. The perceptual input stimulates the neurons in the first, emotion layer. Weights adjustment is also proposed for the interconnected neurons in the feeling layer and between the feeling and mood layer based on Hebbian learning. Experiments are presented to validate the proposed method. Based on the emotional model, the output action such as gestural and facial expressions for the robot is calculated.

Open Access: Yes

DOI: 10.1109/RIISS.2014.7009165

Structured learning for extraction of daily life log measured by smart phone sensors

J. Botzheim Naoyuki Kubota

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2015-01-01

Volume: 30

Issue: Unknown

Page Range: 277-293

Description:

This chapter deals with producing information using structured learning to extract daily life log measured by smart phone sensors. Acceleration, angular velocity, and movement distance are measured by smart phone sensors and stored as the entries of the daily life log together with the activity information and timestamp.First, this chapter introduces the concept of Informationally Structured Space (ISS) and explains how smart phones can be used for collecting data for the daily life log. Then, structured learning is proposed for estimating the human activities based on the time series of the measured data. The method applies growing neural gas for performing clustering on the data, and spiking neural network for estimating the activity. A modified simple spike response model is applied to reduce the computational cost. The external input values of the spiking neurons depend on the growing neurons, and various metrics are investigated in the input calculation.Experiments are performed for verifying the effectiveness of the proposed method. Finally, the future direction on this research is discussed.

Open Access: Yes

DOI: 10.1007/978-3-319-13545-8_16

Gestural and facial communication with smart phone based robot partner using emotional model

J. Botzheim Jinseok Woo Noel Tay Nuo Wi Toru Yamaguchi Naoyuki Kubota

Publication Name: World Automation Congress Proceedings

Publication Date: 2014-10-24

Volume: Unknown

Issue: Unknown

Page Range: 644-649

Description:

When conducting natural communication in addition to perform verbal communication, a robot partner should also understand non-verbal communication such as facial and gestural information. The word 'understand' for the robot means how to grasp the meaning of the gesture itself. In this paper we propose a smart phone based system, where an emotional model connects the facial and gestural communication of a human and a robot partner. The input of the emotional model is based on face classification and gesture recognition from the human side. Based on the emotional model, the output action such as gestural and facial expressions for the robot is calculated.

Open Access: Yes

DOI: 10.1109/WAC.2014.6936076

Computational intelligence for gestural communication using emotional model

J. Botzheim Bakhtiar Yusuf Toru Yamaguchi Naoyuki Kubota

Publication Name: Iwaciii 2013 3rd International Workshop on Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

When conducting natural communication in addition to perform verbal communication, non-verbal communication such as gestural information should also be understood. By the word "understand" we mean not only the recognition of one action, but also grasp the meaning of the gesture itself. Therefore, in order to understand the meaning of an action, in this paper we propose emotional model along with the gesture recognition technique. First we discuss the gesture recognition method using iPhone camera by applying steady state genetic algorithm, spiking neural network and self organizing map. After that we use the gesture recognition result as an input data for the emotional model.

Open Access: Yes

DOI: DOI not available

Cyclic motion generation for intelligent robot by evolutionary computation

J. Botzheim Noriko Takase Naoyuki Kubota

Publication Name: Proceedings of the 2013 IEEE Workshop on Robotic Intelligence in Informationally Structured Space Riiss 2013 2013 IEEE Symposium Series on Computational Intelligence Ssci 2013

Publication Date: 2013-10-31

Volume: Unknown

Issue: Unknown

Page Range: 13-19

Description:

In this paper we propose a method for motion generation of intelligent multi-legged robot using evolutionary computation. Legged robot can walk in various complex terrains such as stairs as well as in flat environment. However, setting the robot's behavior to adapt to various environments in advance is very difficult. The robot can mimic the movement of organisms based on computational intelligence. In this study we apply steady state genetic algorithm for generating the motion sequence of a six-legged robot modeled by forward kinematics. The number of intermediate positions of the motion sequence is adapted to the environment and optimized as well. We use a computer simulation environment before we apply our method in real robot. This can reduce the time spent on finding the optimal parameter settings and the solution itself for the optimization problem. The solution is evaluated mainly on the moving distance of the robot. Experiments were conducted to confirm the proposed technique. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/RiiSS.2013.6607923

Robot edutainment on walking motion of multi-legged robot

J. Botzheim Noriko Takase Naoyuki Kubota

Publication Name: Proceedings 2013 2nd International Conference on Robot Vision and Signal Processing Rvsp 2013

Publication Date: 2013-01-01

Volume: Unknown

Issue: Unknown

Page Range: 229-233

Description:

In this paper we present a short-term robot edutainment for junior high school students. The theme of this robotic course is the walking motion of multi-legged robot. We provided the students with the robot educational material that contains assembled leg parts. The students devised the configuration and motion of the robot using given constraints. We conducted a robot contest for the students to present their results in this robot course. As a result, by using limited materials, the students were able to produce a robot that shows their ingenuity. We could observe from a questionnaire about the course that the students were interested in science and robots. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/RVSP.2013.59

Extraction of daily life log measured by smart phone sensors using neural computing

J. Botzheim Dalai Tang Takenori Obo Bakhtiar Yusuf Toru Yamaguchi Naoyuki Kubota

Publication Name: Procedia Computer Science

Publication Date: 2013-01-01

Volume: 22

Issue: Unknown

Page Range: 883-892

Description:

This paper deals with the information extraction of daily life log measured by smart phone sensors. Two types of neural computing are applied for estimating the human activities based on the time series of the measured data. Acceleration, angular velocity, and movement distance are measured by the smart phone sensors and stored as the entries of the daily life log together with the activity information and timestamp. First, growing neural gas performs clustering on the data. Then, spiking neural network is applied to estimate the activity. Experiments are performed for verifying the effectiveness of the proposed method. © 2013 The Authors.

Open Access: Yes

DOI: 10.1016/j.procs.2013.09.171

Human gesture recognition for robot partners by spiking neural network and classification learning

J. Botzheim Takenori Obo Naoyuki Kubota

Publication Name: 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligence Systems Scis Isis 2012

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1954-1958

Description:

Recently, the rate of elderly people rises in the super-aging society. Human-friendly robots can be used to support the mental and physical care for elderly people and to assist the care of caregivers to elderly people. Robotic conversation can activate the brain of such elderly people and improve their concentration and memory abilities. However, it is difficult for a robot to converse appropriately with a person even if many contents of the conversation are designed in advance because the performance of voice recognition is not enough in the daily conversation. Recognition of human gestures is also important in order to perform smooth communication. This paper deals with human gestures recognition using spiking neural network and classification learning. The proposed method is able to handle the cultural differences in the human communication. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/SCIS-ISIS.2012.6505305

Path planning in probabilistic environment by bacterial memetic algorithm

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2012-12-01

Volume: 14

Issue: Unknown

Page Range: 439-448

Description:

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.

Open Access: Yes

DOI: 10.1007/978-3-642-29934-6_42

Bacterial memetic algorithm for simultaneous optimization of path planning and flow shop scheduling problems

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Artificial Life and Robotics

Publication Date: 2012-10-01

Volume: 17

Issue: 1

Page Range: 107-112

Description:

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.

Open Access: Yes

DOI: 10.1007/s10015-012-0021-9

Bacterial memetic algorithm for offline path planning of mobile robots

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Memetic Computing

Publication Date: 2012-03-01

Volume: 4

Issue: 1

Page Range: 73-86

Description:

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. © 2012 Springer-Verlag.

Open Access: Yes

DOI: 10.1007/s12293-012-0076-0

Path planning for mobile robots by bacterial memetic algorithm

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: IEEE Ssci 2011 Symposium Series on Computational Intelligence Riiss 2011 2011 IEEE Workshop on Robotic Intelligence in Informationally Structured Space

Publication Date: 2011-08-12

Volume: Unknown

Issue: Unknown

Page Range: 107-112

Description:

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.

Open Access: Yes

DOI: 10.1109/RIISS.2011.5945787