KOMUNIKASI ANTAR ROBOT SEPAKBOLA BERODA MENGGUNAKAN UDP MULTICAST

Kontes Robot Indonesia pada tahun 2017 membuka divisi baru, yaitu Kontes Robot Sepakbola Indonesia Beroda atau bisa disebut KRSBI-B. KRSBI-B adalah perlombaan sepakbola antar robot beroda. Untuk memenangkan pertandingan, setiap tim harus menyiapkan hardware, algoritma, dan strategi yang baik. Strategi merupakan aspek yang sangat penting di KRSBI-B. Strategi tidak akan bisa berjalan tanpa adanya komunikasi antar pemainnya. Oleh karena itu, di dalam penelitian ini akan dibahas mengenai komunikasi dan koordinasi antar robot sepakbola beroda. Setiap tim robot minimal menurunkan tiga robot dalam pertandingan, yaitu Striker, Mid Fielder, dan Goal Keeper. Komunikasi dalam pertandingan ini, selain digunakan untuk mengatur strategi, juga untuk mendengarkan perintah aplikasi wasit dari juri, yaitu Referee Box. Juri mengharuskan ada satu komputer yang digunakan untuk mem-forward pesan Referee Box ke semua robot dan mengatur strategi robot, yaitu Base Station. Base Station akan tersambung dengan Referee Box menggunakan TCP. Tiga robot dan Base Station akan tersambung menggunakan UDP Multicast. Base Station akan mengirimkan status Referee Box dan setiap robot akan mengirimkan status dirinya. Referee Box dan robot akan mengirimkan statusnya masing-masing setiap 100 milidetik ke multicast group. Dengan diketahuinya status pertandingan dan status masing-masing robot, maka strategi dapat dilakukan. Berdasarkan hasil pengujian, semua data Referee Box dan data masing-masing robot berhasil sampai di multicast group. Strategi pun sukses dilakukan, karena komunikasi yang dilakukan berjalan dengan lancar. Dengan demikian, dapat ditarik kesimpulan bahwa komunikasi dan strategi antar robot berhasil dilakukan.Kata Kunci: robot, sepak bola, multicast, UD

Can robots possess knowledge? : Rethinking the DIK(W) pyramid through the lens of employees of an automotive factory

Knowledge, information, and data are increasingly processed in human–robot collaboration. This study tackles two requirements for revising the concepts of knowledge, information, and data. First is developing robots’ knowledge capabilities and transparency and ensuring effective division of tasks between humans and robots to increase the productivity of robotised factories. Employees’ interpretations of robots’ abilities to possess knowledge reveal their assumptions of robots’ possibilities and limitations to create knowledge-based products with humans. Second, the classic DIK(W) pyramid of data, information, knowledge, and wisdom is a theoretical construct requiring additional empirical research. This empirical exploratory study develops the DIK(W) further and applies it as a tool to understand employees’ perspectives of robots and knowledge. Do people believe robots possess knowledge? What kind of knowledge can (or cannot) robots possess? A survey (n = 269) was collected from the most robotised factory in Finland, Valmet Automotive. Half of the respondents think robots can possess knowledge, but only with humans. These respondents were more likely to trust robots compared to those who think robots cannot possess knowledge. As the key contribution, the DIK(W) pyramid is reconceived by (i) acknowledging robots and humans, (ii) turning the pyramid upside down, and (iii) recognising knowledge as a dividing concept.© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visithttp://creativecommons.org/licenses/by/4.0/.I thank Olli Nevalainen for collecting the survey. The research was funded by the Academy of Finland, project nr. 319872 Second Machine Age Knowledge Co-Creation Processes in Space and Time.fi=vertaisarvioitu|en=peerReviewed

Co-creating Knowledge with Robots: System, Synthesis, and Symbiosis

In the contemporary robotizing knowledge economy, robots take increasing responsibility for accomplishing knowledge-related tasks that so far have been in the human domain. This profoundly changes the knowledge-creation processes that are at the core of the knowledge economy. Knowledge creation is an interactive spatial process through which ideas are transformed into new and justified outcomes, such as novel knowledge and innovations. However, knowledge-creation processes have rarely been studied in the context of human–robot co-creation. In this article, we take the perspective of key actors who create the future of robotics, namely, robotics-related students and researchers. Their thoughts and actions construct the knowledge co-creation processes that emerge between humans and robots. We ask whether robots can have and create knowledge, what kind of knowledge, and what kind of spatialities connect to interactive human–robot knowledge-creation processes. The article’s empirical material consists of interviews with 34 robotics-related researchers and students at universities in Finland and Singapore as well as observations of human–robot interactions there. Robots and humans form top-down systems, interactive syntheses, and integrated symbioses in spatial knowledge co-creation processes. Most interviewees considered that robots can have knowledge. Some perceived robots as machines and passive agents with rational knowledge created in hierarchical systems. Others saw robots as active actors and learning co-workers having constructionist knowledge created in syntheses. Symbioses integrated humans and robots and allowed robots and human–robot cyborgs access to embodied knowledge.© The Author(s) 2022. Published by Springer. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.fi=vertaisarvioitu|en=peerReviewed

Robot Team Formation Control Using Communication Throughput Approach

In this thesis, we consider a team of robots forming a mobile robot network cooperating to accomplish a mission in an unknown but structured environment. The team has no a-priori knowledge of the environment. Robots have limited memory storage capabilities, not enough to map the environment. Each robot also has limited sensor capability and computational power. Due to the need to avoid obstacles and other environment effects, some robots get delayed from the rest. Using tracking controller, the robot team should follow the leader in a flexible formation shape without losing network connectivity, and that was achieved by monitoring the end-to-end throughput level

The Penetration of Internet of Things in Robotics: Towards a Web of Robotic Things

As the Internet of Things (IoT) penetrates different domains and application areas, it has recently entered also the world of robotics. Robotics constitutes a modern and fast-evolving technology, increasingly being used in industrial, commercial and domestic settings. IoT, together with the Web of Things (WoT) could provide many benefits to robotic systems. Some of the benefits of IoT in robotics have been discussed in related work. This paper moves one step further, studying the actual current use of IoT in robotics, through various real-world examples encountered through a bibliographic research. The paper also examines the potential ofWoT, together with robotic systems, investigating which concepts, characteristics, architectures, hardware, software and communication methods of IoT are used in existing robotic systems, which sensors and actions are incorporated in IoT-based robots, as well as in which application areas. Finally, the current application of WoT in robotics is examined and discussed

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future