@inproceedings{1c7d53de201d47048dcc49ffc5681d49,
title = "Obstacle Avoidance by a Mobile Platform Using an Ultrasound Sensor",
abstract = "The problems of obstacle avoidance occur in many areas for autonomous vehicles. In automotive field, Advanced Driver Assistance Systems modules equipped with sensor fusion are used to resolve these problems. In the case of small mobile platforms, electronic sensors such as ultrasound, gyroscopes, magnetometers and encoders are commonly used. The data obtained from these sensors is measured and processed, which permits the development of automatic obstacle avoidance functions for mobile platforms. The information from these sensors is sufficient to detect obstacles, determine the distance to obstacles and prepare actions to avoid the obstacles. This paper presents the results of research on two obstacle avoidance algorithms that were prepared for small mobile platforms that take advantage of an ultrasonic sensor. The presented solutions are based on calculating the weights of the possible directions for obstacle avoidance and the geometric analysis of an obstacle.",
keywords = "ADAS, Detection the obstacle, Obstacle avoidance, Sensors",
author = "Adam Ziebinski and Rafal Cupek and Marek Nalepa",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 9th International Conference on Computational Collective Intelligence, ICCCI 2017 ; Conference date: 27-09-2017 Through 29-09-2017",
year = "2017",
doi = "10.1007/978-3-319-67077-5\_23",
language = "English",
isbn = "9783319670768",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "238--248",
editor = "Piotr Jedrzejowicz and Gottfried Vossen and Papadopoulos, \{George A.\} and Nguyen, \{Ngoc Thanh\} and Bogdan Trawinski",
booktitle = "Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings",
address = "Germany",
}