IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Unpredicted Trajectories of an Automated Guided Vehicle with Chaos

Unpredicted Trajectories of an Automated Guided Vehicle with Chaos
View Sample PDF
Author(s): Magda Judith Morales Tavera (Universidade Federal do Rio de Janeiro, Brazil), Omar Lengerke (Universidad Autónoma de Bucaramanga, Colombia)and Max Suell Dutra (Universidade Federal do Rio de Janeiro, Brazil)
Copyright: 2014
Pages: 8
Source title: Robotics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-4607-0.ch048

Purchase

View Unpredicted Trajectories of an Automated Guided Vehicle with Chaos on the publisher's website for pricing and purchasing information.

Abstract

Intelligent Transportation Systems (ITS) are the future of transportation. As a result of emerging standards, vehicles will soon be able to talk to one another as well as their environment. A number of applications will be made available for vehicular networks that improve the overall safety of the transportation infrastructure. This chapter develops a method to impart chaotic motions to an Automated Guided Vehicle (AGV). The chaotic AGV implies a mobile robot with a controller that ensures chaotic motions. This kind of motion is characterized by the topological transitivity and the sensitive dependence on initial conditions. Due the topological transitivity, the mobile robot is guaranteed to scan the whole connected workspace. For scanning motion, the chaotic robot neither requires a map of the workspace nor plans global motions. It only requires the measurement of the workspace boundary when it comes close to it.

Related Content

Rashmi Rani Samantaray, Zahira Tabassum, Abdul Azeez. © 2024. 32 pages.
Sanjana Prasad, Deepashree Rajendra Prasad. © 2024. 25 pages.
Deepak Varadam, Sahana P. Shankar, Aryan Bharadwaj, Tanvi Saxena, Sarthak Agrawal, Shraddha Dayananda. © 2024. 24 pages.
Tarun Kumar Vashishth, Vikas Sharma, Kewal Krishan Sharma, Bhupendra Kumar, Sachin Chaudhary, Rajneesh Panwar. © 2024. 29 pages.
Mrutyunjaya S. Hiremath, Rajashekhar C. Biradar. © 2024. 30 pages.
C. L. Chayalakshmi, Mahabaleshwar S. Kakkasageri, Rajani S. Pujar, Nayana Hegde. © 2024. 30 pages.
Amit Kumar Tyagi. © 2024. 29 pages.
Body Bottom