P-AgNav: Range View-Based Autonomous Navigation System for Cornfields

In this paper, we present an in-row and under-canopy autonomous navigation system for cornfields, called the Purdue Agricultural Navigation System or P-AgNav. Our navigation framework is primarily based on range view images from a 3D light detection and ranging (LiDAR) sensor. P-AgNav is designed fo...

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Vydané v:IEEE robotics and automation letters Ročník 10; číslo 4; s. 3366 - 3373
Hlavní autori: Kim, Kitae, Deb, Aarya, Cappelleri, David J.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.04.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract In this paper, we present an in-row and under-canopy autonomous navigation system for cornfields, called the Purdue Agricultural Navigation System or P-AgNav. Our navigation framework is primarily based on range view images from a 3D light detection and ranging (LiDAR) sensor. P-AgNav is designed for an autonomous robot to navigate in the corn rows with collision avoidance and to switch between rows without GNSS assistance or pre-defined waypoints. The system enables robots, which are intended to monitor crops or conduct physical sampling, to autonomously navigate multiple crop rows with minimal human intervention, thereby increasing crop management efficiency. The capabilities of P-AgNav have been validated through experiments in both simulation and real cornfield environments.
AbstractList In this paper, we present an in-row and under-canopy autonomous navigation system for cornfields, called the Purdue Agricultural Navigation System or P-AgNav. Our navigation framework is primarily based on range view images from a 3D light detection and ranging (LiDAR) sensor. P-AgNav is designed for an autonomous robot to navigate in the corn rows with collision avoidance and to switch between rows without GNSS assistance or pre-defined waypoints. The system enables robots, which are intended to monitor crops or conduct physical sampling, to autonomously navigate multiple crop rows with minimal human intervention, thereby increasing crop management efficiency. The capabilities of P-AgNav have been validated through experiments in both simulation and real cornfield environments.
Author Deb, Aarya
Kim, Kitae
Cappelleri, David J.
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SubjectTerms agricultural automation
Autonomous navigation
Autonomous robots
Collision avoidance
Crops
Feature extraction
Laser radar
Lidar
Navigation
Navigation systems
Point cloud compression
Robotics and automation in agriculture and forestry
Robots
Switches
Three-dimensional displays
Title P-AgNav: Range View-Based Autonomous Navigation System for Cornfields
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