The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Self Control and Server-Supervisory Control for Multiple Mobile Robots, and its Applicability to Intelligent DNC System
|
|
Author(s): F. Nagata (Tokyo University of Science, Japan), T. Yamashiro (Tokyo University of Science, Japan), N. Kitahara (Tokyo University of Science, Japan), A. Otsuka (Tokyo University of Science, Japan), K. Watanabe (Okayama University, Japan)and Maki K. Habib (The American University in Cairo, Egypt)
Copyright: 2012
Pages: 18
Source title:
Computational Methods for Optimizing Manufacturing Technology: Models and Techniques
Source Author(s)/Editor(s): J. Paulo Davim (University of Aveiro, Portugal)
DOI: 10.4018/978-1-4666-0128-4.ch003
Purchase
|
Abstract
Multiple mobile robots with six PSD (Position Sensitive Detector) sensors are designed for experimentally evaluating the performance of two control systems. They are self-control mode and server-supervisory control mode. The control systems are considered to realize swarm behaviors such as Ligia exotica. This is done by using only information of PSD sensors. Experimental results show basic but important behaviors for multiple mobile robots. They are following, avoidance, and schooling behaviors. The collective behaviors such as following, avoidance, and schooling emerge from the local interactions among the robots and/or between the robots and the environment. The objective of the study is to design an actual system for multiple mobile robots, to systematically simulate the behaviors of various creatures who form groups such as a school of fish or a swarm of insect. Further, the applicability of the server-supervisory control scheme to an intelligent DNC (Direct Numerical Control) system is briefly considered for future development. DNC system is an important peripheral apparatus, which can directly control NC machine tools. However, conventional DNC systems can neither deal with various information transmitted from different kinds of sensors through wireless communication nor output suitable G-codes by analyzing the sensors information in real time. The intelligent DNC system proposed at the end of the chapter aims to realize such a novel and flexible function with low cost.
Related Content
|
Poshan Yu, Zixuan Zhao, Emanuela Hanes.
© 2023.
29 pages.
|
|
Subramaniam Meenakshi Sundaram, Tejaswini R. Murgod, Madhu M. Nayak, Usha Rani Janardhan, Usha Obalanarasimhaiah.
© 2023.
20 pages.
|
|
Rekha R. Nair, Tina Babu, Kishore S..
© 2023.
23 pages.
|
|
Wasswa Shafik.
© 2023.
22 pages.
|
|
Jay Kumar Jain, Dipti Chauhan.
© 2023.
24 pages.
|
|
George Makropoulos, Dimitrios Fragkos, Harilaos Koumaras, Nancy Alonistioti, Alexandros Kaloxylos, Vaios Koumaras, Theoni Dounia, Christos Sakkas, Dimitris Tsolkas.
© 2023.
19 pages.
|
|
Shouvik Sanyal, Kalimuthu M., Thangaraja Arumugam, Aruna R., Balaji J., Ajitha Savarimuthu, Chandan Chavadi, Dhanabalan Thangam, Sendhilkumar Manoharan, Shasikala Patil.
© 2023.
17 pages.
|
|
|