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What is Map-Based Approach

Chapter 8
Industry 4.0 and Hyper-Customized Smart Manufacturing Supply Chains
The navigation system of mobile robot in which the environment details are given in the form of graph and grid models. Using that models the system identify where the robot or AGV are located in the environment. In vision navigation early stages, the knowledge of environment is represent in 2D projection normally called occupancy map.
Published in Chapter:
Autonomous Vehicle in Industrial Logistics Application: Case Study
Julius Fusic S. (Thiagarajar College of Engineering, India), Kanagaraj G. (Thiagarajar College of Engineering, India), and Hariharan K. (Thiagarajar College of Engineering, India)
Copyright: © 2019 |Pages: 27
DOI: 10.4018/978-1-5225-9078-1.ch008
Abstract
Rapid technological advances have revolutionized the industrial sector. In the global market, it is necessary to consider the new paradigm of Industry 4.0 that presents a lot of features in the industrial logistics application. It has been seen through literature that innovation management practices enable companies to compete within the autonomous and connected vehicle market and is considered as an emerging and competitive differentiator towards the growth of the product and that of meeting customer demands within the changing markets. The first case study explores the integration of GPS and GLONASS signals in AGV for localization and navigation of customer destination and materials in the indoor and outdoor environment. The second case study implemented in obstacle environment that recognized the obstacle in front of the robot and also identified the dimension of the obstacle size, length, width, circumference, height, and distance from a robot. The strength and disadvantages of the system are discussed in the logistical application and future outlines are provided.
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