Vision System for a Forestry Navigation Machine

This article presents the development of a vision system designed to enhance the autonomous navigation capabilities of robots in complex forest environments. Leveraging RGBD and thermic cameras, specifically the Intel RealSense 435i and FLIR ADK, the system integrates diverse visual sensors with adv...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 24; no. 5; p. 1475
Main Authors: Pereira, Tiago, Gameiro, Tiago, Pedro, José, Viegas, Carlos, Ferreira, N. M. Fonseca
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 24.02.2024
MDPI
Subjects:
Algorithms
Automation
autonomous mobile robot
Cameras
Datasets
Decision making
Forestry
Forests and forestry
Image processing
image processing algorithms
International economic relations
Neural networks
object detection
Robotics
Robots
Semiconductor industry
Sensors
Vegetation
vision system
Vision systems
YOLOv5
United States
United States > US
image processing algorithms
autonomous mobile robot
vision system
object detection
YOLOv5
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:This article presents the development of a vision system designed to enhance the autonomous navigation capabilities of robots in complex forest environments. Leveraging RGBD and thermic cameras, specifically the Intel RealSense 435i and FLIR ADK, the system integrates diverse visual sensors with advanced image processing algorithms. This integration enables robots to make real-time decisions, recognize obstacles, and dynamically adjust their trajectories during operation. The article focuses on the architectural aspects of the system, emphasizing the role of sensors and the formulation of algorithms crucial for ensuring safety during robot navigation in challenging forest terrains. Additionally, the article discusses the training of two datasets specifically tailored to forest environments, aiming to evaluate their impact on autonomous navigation. Tests conducted in real forest conditions affirm the effectiveness of the developed vision system. The results underscore the system’s pivotal contribution to the autonomous navigation of robots in forest environments.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s24051475