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1 – 10 of 92The shortage of Chinese language teachers have been identified as a pressing issue globally. This paper aims to respond to the needs by investigating and designing the learning…
Abstract
Purpose
The shortage of Chinese language teachers have been identified as a pressing issue globally. This paper aims to respond to the needs by investigating and designing the learning innovation with autonomous programmable robot, NAO.
Design/methodology/approach
By thoughtfully embedding NAO robot into teaching basic Chinese language, this research demonstrates an inquiry qualitative case study of artificial intelligence design principles and learning engagement with rule-based reasoning and progress test design.
Findings
This state-of-the arts robot use its emotion recognition and body language automated (LED eye with various colours) to demonstrate the Chinese words, to increase learners’ understanding and enhance their memory of the words learned. The responses conclude that the novel learning experience is more fun and interesting, thus the engagement from the axis of novelty, interactivity, motivation and interest is enhanced.
Research limitations/implications
It is recognised that the number of research participants was small, but the qualitative finding demonstrate key issues and recommendation that may inspire future empirical research.
Practical implications
Today, robotics is a rapidly growing field and has received significant attention in education. Humanoid robots are now increasingly used in fields such as education, hospitality, entertainment and health care. Educational robots are anticipated to serve as teaching assistants.
Originality/value
The learning engagement paradigm has shifted from manual engagement to personal response systems or mixed-reality on mobile platforms, and now with the humanoid robot, the recommendation of four principles and future work and for designing humanoid robot as a language tutor are discussed. The educational robot model can be changed to a newer robot such as CANBOT U05E.
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Hamed Shahbazi, Kamal Jamshidi and Amir Hasan Monadjemi
The purpose of this paper is to model a motor region named the mesencephalic locomotors region (MLR) which is located in the end part of the brain and first part of the spinal…
Abstract
Purpose
The purpose of this paper is to model a motor region named the mesencephalic locomotors region (MLR) which is located in the end part of the brain and first part of the spinal cord. This model will be used for a Nao soccer player humanoid robot. It consists of three main parts: High Level Decision Unit (HLDU), MLR‐Learner and the CPG layer. The authors focus on a special type of decision making named curvilinear walking.
Design/methodology/approach
The authors' model is based on stimulation of some programmable central pattern generators (PCPGs) to generate curvilinear bipedal walking patterns. PCPGs are made from adaptive Hopfs oscillators. High level decision, i.e. curvilinear bipedal walking, will be formulated as a policy gradient learning problem over some free parameters of the robot CPG controller.
Findings
The paper provides a basic model for generating different types of motions in humanoid robots using only simple stimulation of a CPG layer. A suitable and fast curvilinear walk has been achieved on a Nao humanoid robot, which is similar to human ordinary walking. This model can be extended and used in other types of humanoid.
Research limitations/implications
The authors' work is limited to a special type of biped locomotion. Different types of other motions are encouraged to be tested and evaluated by this model.
Practical implications
The paper introduces a bio‐inspired model of skill learning for humanoid robots. It is used for curvilinear bipedal walking pattern, which is a beneficial movement in soccer‐playing Nao robots in Robocup competitions.
Originality/value
The paper uses a new biological motor concept in artificial humanoid robots, which is the mesencephalic locomotor region.
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This paper aims to deal with the problem of designing robot behaviors (mainly to robotic arms) to express emotions. The authors study the effects of robot behaviors from our…
Abstract
Purpose
This paper aims to deal with the problem of designing robot behaviors (mainly to robotic arms) to express emotions. The authors study the effects of robot behaviors from our humanoid robot NAO on the subject’s emotion expression in human–robot interaction (HRI).
Design/methodology/approach
A method to design robot behavior through the movement primitives is proposed. Then, a novel dimensional affective model is built. Finally, the concept of action semantics is adopted to combine the robot behaviors with emotion expression.
Findings
For the evaluation of this combination, the authors assess positive (excited and happy) and negative (frightened and sad) emotional patterns on 20 subjects which are divided into two groups (whether they were familiar with robots). The results show that the recognition of the different emotion patterns does not have differences between the two groups and the subjects could recognize the robot behaviors with emotions.
Practical implications
Using affective models to guide robots’ behavior or express their intentions is highly beneficial in human–robot interaction. The authors think about several applications of the emotional motion: improve efficiency in HRI, direct people during disasters, better understanding with human partners or help people perform their tasks better.
Originality/value
This paper presents a method to design robot behaviors with emotion expression. Meanwhile, a similar methodology can be used in other parts (leg, torso, head and so on) of humanoid robots or non-humanoid robots, such as industrial robots.
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Abhishek Kumar Kashyap and Dayal R. Parhi
This paper aims to outline and implement a novel hybrid controller in humanoid robots to map an optimal path. The hybrid controller is designed using the Owl search algorithm…
Abstract
Purpose
This paper aims to outline and implement a novel hybrid controller in humanoid robots to map an optimal path. The hybrid controller is designed using the Owl search algorithm (OSA) and Fuzzy logic.
Design/methodology/approach
The optimum steering angle (OS) is used to deal with the obstacle located in the workspace, which is the output of the hybrid OSA Fuzzy controller. It is obtained by feeding OSA's output, i.e. intermediate steering angle (IS), in fuzzy logic. It is obtained by supplying the distance of obstacles from all directions and target distance from the robot's present location.
Findings
The present research is based on the navigation of humanoid NAO in complicated workspaces. Therefore, various simulations are performed in a 3D simulator in different complicated workspaces. The validation of their outcomes is done using the various experiments in similar workspaces using the proposed controller. The comparison between their outcomes demonstrates an acceptable correlation. Ultimately, evaluating the proposed controller with another existing navigation approach indicates a significant improvement in performance.
Originality/value
A new framework is developed to guide humanoid NAO in complicated workspaces, which is hardly seen in the available literature. Inspection in simulation and experimental workspaces verifies the robustness of the designed navigational controller. Considering minimum error ranges and near collaboration, the findings from both frameworks are evaluated against each other in respect of specified navigational variables. Finally, concerning other present approaches, the designed controller is also examined, and major modifications in efficiency have been reported.
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Huaqing Min, Chang'an Yi, Ronghua Luo and Jinhui Zhu
This paper aims to present a hybrid control approach that combines learning-based reactive control and affordance-based deliberate control for autonomous mobile robot navigation…
Abstract
Purpose
This paper aims to present a hybrid control approach that combines learning-based reactive control and affordance-based deliberate control for autonomous mobile robot navigation. Unlike many current navigation approaches which only use learning-based paradigms, the authors focus on how to utilize the machine learning methods for reactive control together with the affordance knowledge that is simultaneously inherent in natural environments to gain advantages from both local and global optimization.
Design/methodology/approach
The idea is to decompose the complex and large-scale robot navigation task into multiple sub-tasks and use the hierarchical reinforcement learning (HRL) algorithm, which is well-studied in the learning and control algorithm domains, to decompose the overall task into sub-tasks and learn a grid-topological map of the environment. An affordance-based deliberate controller is used to inspect the affordance knowledge of the obstacles in the environment. The hybrid control architecture is then designed to integrate the learning-based reactive control and affordance-based deliberate control based on the grid-topological and affordance knowledge.
Findings
Experiments with computer simulation and an actual humanoid NAO robot have demonstrated the effectiveness of the proposed hybrid approach for mobile robot navigation.
Originality/value
The main contributions of this paper are a new robot navigation framework that decomposes a complex navigation task into multiple sub-tasks using the HRL approach, and hybrid control architecture development that integrates learning-based and affordance-based paradigms for autonomous mobile robot navigation.
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Maria Jose Galvez Trigo, Penelope Jane Standen and Sue Valerie Gray Cobb
The purpose of this paper is to identify the main reasons for low uptake of robots in special education (SE), obtained from an analysis of previous studies that used robots in the…
Abstract
Purpose
The purpose of this paper is to identify the main reasons for low uptake of robots in special education (SE), obtained from an analysis of previous studies that used robots in the area, and from interviewing SE teachers about the topic.
Design/methodology/approach
An analysis of 18 studies that used robots in SE was performed, and the conclusions were complemented and compared with the feedback from interviewing 13 SE teachers from Spain and the UK about the reasons they believed caused the low uptake of robots in SE classrooms.
Findings
Five main reasons why SE schools do not normally use robots in their classrooms were identified: the inability to acquire the system due to its price or availability; its difficulty of use; the low range of activities offered; the limited ways of interaction offered; and the inability to use different robots with the same software.
Originality/value
Previous studies focussed on exploring the advantages of using robots to help children with autism spectrum conditions and learning disabilities. This study takes a step further and looks into the reasons why, despite the benefits shown, robots are rarely used in real-life settings after the relevant study ends. The authors also present a potential solution to the issues found: involving end users in the design and development of new systems using a user-centred design approach for all the components, including methods of interaction, learning activities and the most suitable type of robots.
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Ting Wang, Dominik M. Ramik, Christophe Sabourin and Kurosh Madani
Different machines are already present in the human environment, easing human beings' daily life. In the future, this tendency will be accentuated by integration of numerous robots…
Abstract
Purpose
Different machines are already present in the human environment, easing human beings' daily life. In the future, this tendency will be accentuated by integration of numerous robots (e.g. wheeled robots, legged robots, humanoid robots, network sensors, etc.) in the human environment. A wide range of applications, such as those dealing with warehouse management, industrial assembling, military applications, daily‐life tasks, can benefit from multi‐robot systems. The purpose of this paper is to propose an intelligent system for industrial robotics in the logistic field, based on collaboration between heterogeneous robots.
Design/methodology/approach
The proposed infrastructure for this multi‐robot system is composed of a robots' network including one humanoid robot, wheeled robots, cameras, and remote computer. All devices can communicate between them by using wireless network. The goal of the humanoid robot is to lead the wheeled robots according to the environment and wheeled robots are used to carry a load. The camera allows providing complementary information about the environment; and thanks to machine learning, this control strategy allows complex tasks to be perormed for these logistic applications.
Findings
This concept is implemented on real robots within the frame of a demonstrator including the above‐mentioned kind of robots. The preliminary results, obtained during experimentations, prove the feasibility of the presented strategy for real applications.
Originality/value
The main originalities of this work are, on the one hand, the use of an heterogeneous multi‐robots system for logistic tasks, and on the other hand, the proposed machine learning allows a collaboration task between heterogeneous robots in an autonomous manner.
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Seyed Mohammad Sadegh Khaksar, Bret Slade, Jennifer Wallace and Kaur Gurinder
The purpose of this paper is to address the role of social robots in the education industry, specifically within special developmental schools, as a part of an innovation…
Abstract
Purpose
The purpose of this paper is to address the role of social robots in the education industry, specifically within special developmental schools, as a part of an innovation technology portfolio. It identifies critical success factors (CSFs) arising from the development, adoption and implementation of social robots to educate students with special needs and assist their teachers.
Design/methodology/approach
The study engaged in longitudinal research over 12 months, tracking the role of the Matilda robot in providing educational services to students with special needs.
Findings
The results propose a three-faceted framework for social robot application in special education: development, adoption and implementation.
Originality/value
The study has shown the willingness of students and teachers to embrace social robot technology, and the CSF that arise from this adoption. It has also found that social robots achieve the greatest success within the development, adoption and implementation framework when championed by executive management, and peer teacher support.
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Abhishek Kumar Kashyap and Dayal R. Parhi
Humanoid robots have complicated dynamics, and they lack dynamic stability. Despite having similarities in kinematic structure, developing a humanoid robot with robust walking is…
Abstract
Purpose
Humanoid robots have complicated dynamics, and they lack dynamic stability. Despite having similarities in kinematic structure, developing a humanoid robot with robust walking is quite difficult. In this paper, an attempt to produce a robust and expected walking gait is made by using an ALO (ant lion optimization) tuned linear inverted pendulum model plus flywheel (LIPM plus flywheel).
Design/methodology/approach
The LIPM plus flywheel provides the stabilized dynamic walking, which is further optimized by ALO during interaction with obstacles. It gives an ultimate turning angle, which makes the robot come closer to the obstacle and provide a turning angle that optimizes the travel length. This enhancement releases the constraint on the height of the COM (center of mass) and provides a larger stride. The framework of a sequential locomotion planer has been discussed to get the expected gait. The proposed method has been successfully tested on a simulated model and validated on the real NAO humanoid robot.
Findings
The convergence curve defends the selection of the proposed controller, and the deviation under 5% between simulation and experimental results in regards to travel length and travel time proves its robustness and efficacy. The trajectory of various joints obtained using the proposed controller is compared with the joint trajectory obtained using the default controller. The comparison shows the stable walking behavior generated by the proposed controller.
Originality/value
Humanoid robots are preferred over mobile robots because they can easily imitate the behaviors of humans and can result in higher output with higher efficiency for repetitive tasks. A controller has been developed using tuning the parameters of LIPM plus flywheel by the ALO approach and implementing it in a humanoid robot. Simulations and experiments have been performed, and joint angles for various joints are calculated and compared with the default controller. The tuned controller can be implemented in various other humanoid robots
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