Algorithmic Approaches and Embedded Architectures for Robotic Search and Rescue

被引：2

作者：

Garcia, Manuel ^{[1
]}

Milshteyn, Aleksander ^{[1
]}

Lin, Airs ^{[1
]}

Herman, Garth ^{[1
]}

Rad, Khosrow ^{[1
]}

Liu, Charles ^{[1
]}

Boussalis, Helen ^{[1
]}

机构：

[1] Calif State Univ Los Angeles, Dept Elect & Comp Engn, Univ Res Ctr, Struct Pointing & Control Engn, Los Angeles, CA 90032 USA

来源：

PROCEEDINGS 2017 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI) | 2017年

基金：

美国国家科学基金会;

关键词：

Search and Rescue; Semi-Autonomous Control; Robotics; Computer Vision; Path-finding Algorithms; Hybrid-Routing Algorithms; Eulerian Video Magnification;

D O I：

10.1109/CSCI.2017.71

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Robots facilitate exploration of dangerous environments in response to catastrophic events. Advances in robotic technology have increased their utility and application. Risk in search and rescue operations are greatly reduced due to robotic intervention. Recently Structures, Pointing, and Control Engineering (SPACE) University Research Center (URC) of excellence at California State University of Los Angeles has developed a robotic system for search and rescue. This paper focuses on the development of the algorithms and embedded architecture employed in the system. The Eulerian Video Magnification algorithm was utilized as a means to extract biometric information such as pulse and breathing rate of a human body. The path-finding algorithms were developed for expedite navigation of the robot racing towards the potential victim. A layered model was adopted for the system architecture to facilitate the development and implementation of the designated mobile robot platform.

引用

页码：420 / 425

页数：6

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