Application Of Sampling Based Motion Planning Algorithms In Autonomous Vehicle Navigation
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Application of Sampling-Based Motion Planning Algorithms in Autonomous Vehicle Navigation
With the development of the autonomous driving technology, the autonomous vehicle has become one of the key issues for supporting our daily life and economical activities. One of the challenging research areas in autonomous vehicle is the development of an intelligent motion planner, which is able to guide the vehicle in dynamic changing environments. In this chapter, a novel sampling-based navigation architecture is introduced, which employs the optimal properties of RRT* planner and the low running time property of low-dispersion sampling-based algorithms. Furthermore, a novel segmentation method is proposed, which divides the sampling domain into valid and tabu segments. The resulted navigation architecture is able to guide the autonomous vehicle in complex situations such as takeover or crowded environments. The performance of the proposed method is tested through simulation in different scenarios and also by comparing the performances of RRT and RRT* algorithms. The proposed method provides near-optimal solutions with smaller trees and in lower running time.
Autonomous Vehicle
Autonomous vehicles, despite their relatively short history, have already found practical application in many areas of human activity. Such vehicles are usually replacing people in performing tasks that require long operating time and are held in inaccessible or hazardous environments. Nevertheless, autonomous robotics is probably the area that is being developed the most because of the great demand for such devices in different areas of our lives. This book is a collection of experiences shared by scientists from different parts of the world doing researches and daily exploiting autonomous systems. Giving this book in the hands of the reader, we hope that it will be a treasure trove of knowledge and inspiration for further research in the field of autonomous vehicles.
17th International Conference on Information Technology–New Generations (ITNG 2020)
This volume presents the 17th International Conference on Information Technology—New Generations (ITNG), and chronicles an annual event on state of the art technologies for digital information and communications. The application of advanced information technology to such domains as astronomy, biology, education, geosciences, security, and healthcare are among the themes explored by the ITNG proceedings. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help information flow to end users are of special interest. Specific topics include Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing. The conference features keynote speakers; a best student contribution award, poster award, and service award; a technical open panel, and workshops/exhibits from industry, government, and academia.