Pattern Identification of Robotic Environments using Machine Learning Techniques

被引：2

作者：

Gopalapillai, Radhakrishnan ^{[1
,2
]}

Gupta, Deepa ^{[2
,3
]}

Sudarshan, T. S. B. ^{[1
,2
]}

机构：

[1] Amrita Sch Engn, Dept Comp Sci & Engn, Bengaluru 560035, India

[2] Amrita Univ, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India

[3] Amrita Sch Engn, Dept Math, Bengaluru 560035, India

来源：

7TH INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING & COMMUNICATIONS (ICACC-2017) | 2017年 / 115卷

关键词：

Machine Learning; Time series data; Feature selection; Classification; Object displacement; feature reduction;

D O I：

10.1016/j.procs.2017.09.077

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2017 The Authors. Published by Elsevier B.V.

引用

页码：63 / 71

页数：9

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