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 |
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| Hlavní autori: | , , |
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| Jazyk: | English |
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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. |
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| 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. |
| Author_xml | – sequence: 1 givenname: Kitae orcidid: 0000-0002-8912-9382 surname: Kim fullname: Kim, Kitae email: kim3686@purdue.edu organization: School of Mechanical Engineering, Purdue University, West Lafayette, IN, USA – sequence: 2 givenname: Aarya orcidid: 0000-0002-0147-7965 surname: Deb fullname: Deb, Aarya email: deb8@purdue.edu organization: School of Mechanical Engineering, Purdue University, West Lafayette, IN, USA – sequence: 3 givenname: David J. orcidid: 0000-0001-7222-0625 surname: Cappelleri fullname: Cappelleri, David J. email: dcappell@purdue.edu organization: School of Mechanical Engineering, Purdue University, West Lafayette, IN, USA |
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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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