Computer Vision in Industrial Automation and Mobile Robots

2018 ◽  
pp. 241-266
Author(s):  
Frederico Grilo ◽  
Joao Figueiredo
Keyword(s):  
Computer Vision ◽  
Mobile Robots ◽  
Industrial Automation

Development of a Web-Based Educational Platform to Interact with Remote Mobile Robots

2011 ◽  
pp. 46-65
Author(s):  
Luis Payá ◽  
Oscar Reinoso ◽  
David Úbeda ◽  
Luis M. Jiménez ◽  
José M. Marín
Keyword(s):  
Computer Vision ◽  
Mobile Robots ◽  
Web Based ◽  
Engineering Studies ◽  
Remote Laboratories ◽  
Motivation Interaction ◽  
Basic Concepts ◽  
Basic Features ◽  
And Control ◽  
And Robotics

In this chapter the authors approach the problem that hand-on experiments may present in engineering studies and how Internet has become a powerful tool to improve the students’ motivation, interaction and degree of learning. Also, the authors address some challenges that must be taken into account in order to improve the effectiveness of the remote laboratories. They have implemented an interactive tool so that students can monitor and control the evolution of a team of mobile robots through Internet. This platform is designed for a subject whose contents are computer vision and robotics, and it allows students to learn and practice the basic concepts on those fields and their relationship. In this chapter they present the architecture and basic features of the platform and the experiences collected during the use of it.

Using Global Appearance Descriptors to Solve Topological Visual SLAM

2019 ◽  
pp. 1127-1140
Author(s):  
Lorenzo Fernández Rojo ◽  
Luis Paya ◽  
Francisco Amoros ◽  
Oscar Reinoso
Keyword(s):  
Computer Vision ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Simultaneous Localization And Mapping ◽  
Visual Slam ◽  
Sources Of Information ◽  
Topological Approach ◽  
Unknown Environment ◽  
Localization And Mapping ◽  
Omnidirectional Images

Mobile robots have extended to many different environments, where they have to move autonomously to fulfill an assigned task. With this aim, it is necessary that the robot builds a model of the environment and estimates its position using this model. These two problems are often faced simultaneously. This process is known as SLAM (simultaneous localization and mapping) and is very common since when a robot begins moving in a previously unknown environment it must start generating a model from the scratch while it estimates its position simultaneously. This chapter is focused on the use of computer vision to solve this problem. The main objective is to develop and test an algorithm to solve the SLAM problem using two sources of information: (1) the global appearance of omnidirectional images captured by a camera mounted on the mobile robot and (2) the robot internal odometry. A hybrid metric-topological approach is proposed to solve the SLAM problem.

Using Global Appearance Descriptors to Solve Topological Visual SLAM

2018 ◽  
pp. 6894-6905
Author(s):  
Lorenzo Fernández Rojo ◽  
Luis Paya ◽  
Francisco Amoros ◽  
Oscar Reinoso
Keyword(s):  
Computer Vision ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Simultaneous Localization And Mapping ◽  
Visual Slam ◽  
Sources Of Information ◽  
Topological Approach ◽  
Unknown Environment ◽  
Localization And Mapping ◽  
Omnidirectional Images

Nowadays, mobile robots have extended to many different environments, where they have to move autonomously to fulfill an assigned task. With this aim, it is necessary that the robot builds a model of the environment and estimates its position using this model. These two problems are often faced simultaneously. This process is known as SLAM (Simultaneous Localization and Mapping) and is very common since when a robot begins moving in a previously unknown environment it must start generating a model from the scratch while it estimates its position simultaneously. This work is focused on the use of computer vision to solve this problem. The main objective is to develop and test an algorithm to solve the SLAM problem using two sources of information: (a) the global appearance of omnidirectional images captured by a camera mounted on the mobile robot and (b) the robot internal odometry. A hybrid metric-topological approach is proposed to solve the SLAM problem.

scholarly journals A State-of-the-Art Review on Mapping and Localization of Mobile Robots Using Omnidirectional Vision Sensors

2017 ◽  
Vol 2017 ◽  
pp. 1-20 ◽  
Author(s):  
L. Payá ◽  
A. Gil ◽  
O. Reinoso
Keyword(s):  
Computer Vision ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Autonomous Vehicles ◽  
Scientific Community ◽  
Mobile Robotics ◽  
State Of The Art ◽  
Omnidirectional Vision ◽  
Vision Sensors ◽  
Source Of Information

Nowadays, the field of mobile robotics is experiencing a quick evolution, and a variety of autonomous vehicles is available to solve different tasks. The advances in computer vision have led to a substantial increase in the use of cameras as the main sensors in mobile robots. They can be used as the only source of information or in combination with other sensors such as odometry or laser. Among vision systems, omnidirectional sensors stand out due to the richness of the information they provide the robot with, and an increasing number of works about them have been published over the last few years, leading to a wide variety of frameworks. In this review, some of the most important works are analysed. One of the key problems the scientific community is addressing currently is the improvement of the autonomy of mobile robots. To this end, building robust models of the environment and solving the localization and navigation problems are three important abilities that any mobile robot must have. Taking it into account, the review concentrates on these problems; how researchers have addressed them by means of omnidirectional vision; the main frameworks they have proposed; and how they have evolved in recent years.

Using advanced computer vision algorithms on small mobile robots

2006 ◽  
Author(s):  
G. Kogut ◽  
F. Birchmore ◽  
E. Biagtan Pacis ◽  
H. R. Everett
Keyword(s):  
Computer Vision ◽  
Mobile Robots ◽  
Advanced Computer
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