Technological breakthroughs, combined with the demographic challenges of an aging population and the aftermath of the COVID-19 pandemic, spur new business opportunities in the service robot industry. From a management perspective, these technologies are positively evaluated in terms of increasing productivity, new business opportunities, and financial benefits (Belanche et al., 2020). However, although automation and robotics have already gained attention in the tourism and hospitality industry, research on their use in restaurants and the customer's attitude toward these new service solutions is still limited (Berezina et al., 2019; Ivanov et al., 2019; Kuo et al., 2017).

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on indoor mobile robot position recognition and driving experiment using QR Code during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on the driving control of indoor mobile robot during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on experimental environments for testbeds during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on the QR Code recognition mobile robotics study during the development of QR Code-aware indoor mobility robots.

Recently, there is a great attention and interest in robotics and artificial intelligence technology in various research field including agriculture and life science due to its high functionality and potentiality. In this talk, I will present several agricultural robotics projects progressing in my research group, Human-centered Robotics and Automation Laboratory. In details, the following four researches will be introduced in focus with swarm robotics, simultaneously localization and mapping, and deep learning technologies: 1) multiple agricultural unmanned aerial vehicles; 2) intelligent autonomous spraying vehicle; 3) autonomous unmanned aerial vehicle based small insect tracking and mapping system; and 4) autonomous cooperation of heterogeneous agricultural robots.

In Peru, according to the Census of Students (ECE) carried out by the Ministry of Education at 2016 (MINEDU), there are sustained differences between learning goals in rural and urban schools. There are more than 20 thousand educational robotic kits distributed nationwide. It requires trained teachers to develop their digital competence and integrate these resources into the teaching-learning process. In this context, a virtual course was designed and executed, showing rural teachers how to plan learning sessions that integrate Information and Communication Technologies (ICT) in their pedagogical practice. The course was validated with 2500 registered teachers. In the first court, 300 did not log into the virtual classroom, 500 did not to complete the course, 1170 remained active, 534 successfully completed the course and 473 gained a certificate through the virtual platform. In the second court, there are 667-registered teachers. The conclusions of the experience indicate that it is possible to implement strategies for electronic learning aimed at rural teachers in a sustainable and cost - effective way using ICT, which spontaneously create virtual communities of collaborative learning, which support the process allowing implementation the "Knowledge Management". This experience will allow us to make recommendations for rural education policy in Peru (Fernández Morales, Iriarte Gómez, Mejía Solano, & Revuelta Domínguez, 2017).

The purpose of this study is to investigate the interrelationships among customer perceived value, customer satisfaction, and switching costs as antecedents of customer loyalty in business-to-business (B2B) contexts. Customer loyalty influences firms’ performance as a key source of competitive advantage. Customer loyalty is essential in B2B contexts, although many studies of customer loyalty have focused on the business-to-consumer (B2C) context. Recently, the use of robotics in the industrial marketing environment has become increasingly prevalent. Given the prevalence of robotics in B2B contexts and the importance of customer loyalty, this study investigates the impacts of robotics in industrial marketing relationships, customer perceived value, customer satisfaction, and switching costs on enhancing customer loyalty.

Recently, the interest in the educational robotics has grown greatly, but few studies have been conducted in this field. This study intended to investigate the trend of usage robotics in education during the period of 2001-2014 while analyzing 133 research papers to find the answers to the following questions. First, what is the general research trend of utilizing robotics in education? Second, what are the most recent issues and challenges of robotics in education? Publications have been analyzed using quantitative analysis and cross-tabulation. All gathered articles have been categorized and analyzed under twelve categories. Furthermore, seven categories have been cross-tabulated with other categories. Overall findings present that there are a significant amount of publications on higher and secondary education. Articles on early education and teachers training have started to become more apparent lately. It has also been noticed that robotics generally is seen as an extracurricular activity. Among educational robots, ‘robot kit’ type was one of the highly utilized, especially LEGO Mindstorms robot kit. The main objective of most analyzed articles is the experience of a course curriculum. Results of the study show that there are three main issues and challenges of robotics in education. First, there is a lack of quantitative research on the impact of robotics in education. Second is an absence of well-defined curriculum for target audience. Third is the narrow use of robotics in education. The study also present recommendations for future research.

Robotics technology has been well absorbed into Papert’s constructionist perspective (Papert, 1996) as well as that of Jonassen’s (2000). Robotics allows students to explore creatively, and increases students’ creativity toward computer programming, mechanical designing and constructing, problem solving, collaborating, and motion within an active, enjoyable, and immersive environment, including subjects such as physics, mathematics, and electronics. The principal objectives of this study were to assess the manner in which perceptions of learning robotics and planning lessons through robotics of pre-service elementary teachers could evolve, and to evaluate pre-service elementary teacher program via a case study of a university- based in Korea. This paper introduces a method by which robotics technology might be integrated into a pre-service elementary course, and also includes an analysis of pre-service teachers' robotics activities and their teaching strategy for developing instructions in using robotics.

Accurate estimation of pest density is a prerequisite in achieving efficient pest management. An automatic pest detection system with image processing was installed on a robot to recognize brown marmorated stink bug (Halyomorphahalys) on leaves of paprika(Capsicumannuumvar.angulosum). The shape of pest was recognized and subsequently the robot arm was moved toward the leaves to spray pesticides. The detection system was efficient along with increasing population densities increased. The robot with image processing system was useful for estimating population densities in spatial and temporal domain efficiently.

Accurate estimation of insect density is essential for effective pest management. A simple robotics and image processing system were combined to automatically recognize the density of whiteflies. Subsequently the robot arm was utilized to spray the pesticides in the area of infestation in a minimized amount. The estimated densities of samples in the laboratory condition were in accordance with the actual values. The detection system was efficient when the whitefly densities were at medium to high levels. The results of the present study indicate that the robotic and image processing integration system described here would be useful for evaluating the population dynamics.

Reinforcement learning has been applied to various problems in robotics. However, it was still hard to train complex robotic manipulation tasks since there is a few models which can be applicable to general tasks. Such general models require a lot of training episodes. In these reasons, deep neural networks which have shown to be good function approximators have not been actively used for robot manipulation task. Recently, some of these challenges are solved by a set of methods, such as Guided Policy Search, which guide or limit search directions while training of a deep neural network based policy model. These frameworks are already applied to a humanoid robot, PR2. However, in robotics, it is not trivial to adjust existing algorithms designed for one robot to another robot. In this paper, we present our implementation of Guided Policy Search to the robotic arms of the Baxter Research Robot. To meet the goals and needs of the project, we build on an existing implementation of Baxter Agent class for the Guided Policy Search algorithm code using the built-in Python interface. This work is expected to play an important role in popularizing robot manipulation reinforcement learning methods on cost-effective robot platforms.

Robots have been widely used for the education in kindergarten and elementary school. In this study, the cognition of parents on robots in education is investigated. The study is conducted by analyzing responses of 105 parents with kindergarten students and elementary schoolchildren. The survey results show that most students who have been taking the robotics education start it fromfive or seven years old. The students were mainly educated in the private institution. Therefore, the parents worry about the lack of professionalism about educational institute and teachers. In conclusion, the systematic curriculums and policy of robotic education are needed for kindergarten students and elementary students.

This paper introduces several mobile robots developed by using LEGO MIDSTORM for experimental studies of robotics engineering education. The first mobile robot is the line tracer robot that tracks a line, which is a prototype of wheel-driven mobile robots. Ultra violet sensors are used to detect and follow the line. The second robot system is a two-wheel balancing robot that is somewhat nonlinear and complex. For the robot to balance, a gyro sensor is used to detect a balancing angle and PD control is used. The last robot system is a combined system of a line tracer and a two-wheel balancing robot. Sensor filtering and control algorithms are tested through experimental studies.

The purpose of this study is to improve robotics education in public education. This study was conducted with 157 secondary school teachers regardless of their gender, age and majors. The results are as follows: First, 68.2% of the respondents (81.2% of the STEM(Science, Technology, Engineering, Mathematics)-related teachers) thought that robotics education should be included in public education because it will be a very important area in the future. Second, 73.3% of respondents (89.3% of the STEM-related teachers) agreed that robotics education will be worth teaching as a regular subject. The most important reason was that they thought the robots would be an excellent tool to initiate their class participation and increase their study motivation. Third, the results from this survey showed that the technology teachers would be the best suitable instructors for robotics education. Lastly, teachers felt a great deal of burden to teach robotics although they thought robotics education was necessary. In order to implement robotics education in public school, teachers think it is necessary to take professional training. In addition, teachers should be supported with the reduction in their workload along with sufficient fundings, educational robots such as LEGO MINDSTORMS, and newly designed teaching materials.

The development of IT technology makes the functions and services of robots be integrated, and thus the robots become more intelligent and useful. As sophisticated usage of robots has evolved, direct communication by human language is necessary to increase the efficiency of their usage. In this paper, we propose a conversational interface platform for integrated service robots using MS Robotics Studio. The proposed platform consists of three types of components: a conversation manager to control the flows of the integrated service robots, a user interface to interact with users, and multiple service robots to perform actions or services. For a test-bed of the proposed platform, we build a schedule manager system and confirm the usability through SUS subject test by comparing the schedule manager system with MS Outlook.