Photometric-Planner for Visual Path Following

Robotic navigation is the aspect of cognition related to robot robust mobility. It combines perception, some knowledge on the environment and a set of goal poses to reliably control the robot during a mission that involves displacement. Vision-based autonomous navigation is an instantiation of the l...

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Bibliographic Details
Published inIEEE sensors journal Vol. 21; no. 10; pp. 11310 - 11317
Main Authors A. Rodriguez Martinez, Eder, Caron, Guillaume, Pegard, Claude, Lara-Alabazares, David
Format Journal Article
LanguageEnglish
Published New York IEEE 15.05.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects
aerial robotics
Automatic
Autonomous navigation
Autonomous robots
Cognition
Computer Science
Computer Vision and Pattern Recognition
direct visual servoing
Engineering Sciences
Indoor environments
Navigation
Navigation systems
Positioning devices (machinery)
Robot control
Robot sensing systems
Robotics
Robots
Trajectory planning
Unmanned aerial vehicles
Vision-based robotic navigation
Visual control
Visual perception
Visual tasks
Visualization
Vision-Based Robotic Navigation
Aerial Robotics
Direct Visual Servoing
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Summary:Robotic navigation is the aspect of cognition related to robot robust mobility. It combines perception, some knowledge on the environment and a set of goal poses to reliably control the robot during a mission that involves displacement. Vision-based autonomous navigation is an instantiation of the latter discipline where visual perception is used to control the robot and to represent the environment. This article presents a vision-based navigation system that uses its onboard camera to navigate and a visual path that represents the scene with a set of images. Being a memory-based system, the navigation is conceived as a concatenation of positioning tasks in the visual servoing scheme. The novelty on the proposed system relies on the generation of the images that compose the visual path. These images are rendered from a preobtained model of the scene. The experiments evaluate the performance of the system over three different scenes, contemplating indoor and outdoor environments, and using an Unmanned Aerial Vehicle as testbed.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2020.3027848