Publication Type:

Conference Paper

Source:

Procedia Computer Science, Elsevier B.V., Volume 115, p.63-71 (2017)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032432752&doi=10.1016%2fj.procs.2017.09.077&partnerID=40&md5=02fd5396fe07c0801569c455686aa59d

Keywords:

Artificial intelligence, Classification (of information), Feature extraction, Feature reduction, Learning algorithms, Learning systems, Machine learning models, Machine learning techniques, Mobile robots, Object displacement, On-board sensors, Pattern identification, Robotic environments, Robotics, Robots, Time series, Time series analysis, Time-series data

Abstract:

<p>Analysis of time series data collected from mobile robots is getting more attention in many application areas. When multiple robots move through an environment to perform certain actions, an understanding of the environment viewed by each robot is essential. This paper presents analysis of robotic data using machine learning techniques when the data consist of multiple views of the environment. Robotic environments have been classified using the data captured by onboard sensors of mobile robots using a set of machine learning algorithms and their performances have been compared The machine learning model is validated using a test environment where some of the objects are displaced or removed from their designated position. © 2017 The Author(s).</p>

Notes:

cited By 0; Conference of 7th International Conference on Advances in Computing and Communications, ICACC 2017 ; Conference Date: 22 August 2017 Through 24 August 2017; Conference Code:131212

Cite this Research Publication

R. Gopalapillai, Gupta, D., and Tsb, S., “Pattern Identification of Robotic Environments using Machine Learning Techniques”, in Procedia Computer Science, 2017, vol. 115, pp. 63-71.

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