TY - GEN
T1 - CropNav
T2 - 2023 IEEE International Conference on Robotics and Automation, ICRA 2023
AU - Gasparino, Mateus V.
AU - Higuti, Vitor A.H.
AU - Sivakumar, Arun N.
AU - Velasquez, Andres E.B.
AU - Becker, Marcelo
AU - Chowdhary, Girish
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Small robots that can operate under the plant canopy can enable new possibilities in agriculture. However, unlike larger autonomous tractors, autonomous navigation for such under canopy robots remains an open challenge because Global Navigation Satellite System (GNSS) is unreliable under the plant canopy. We present a hybrid navigation system that autonomously switches between different sets of sensing modalities to enable full field navigation, both inside and outside of crop. By choosing the appropriate path reference source, the robot can accommodate for loss of GNSS signal quality and leverage row-crop structure to autonomously navigate. However, such switching can be tricky and difficult to execute over scale. Our system provides a solution by automatically switching between an exteroceptive sensing based system, such as Light Detection And Ranging (LiDAR) row-following navigation and waypoints path tracking. In addition, we show how our system can detect when the navigate fails and recover automatically extending the autonomous time and mitigating the necessity of human intervention. Our system shows an improvement of about 750 m per intervention over GNSS-based navigation and 500 m over row following navigation.
AB - Small robots that can operate under the plant canopy can enable new possibilities in agriculture. However, unlike larger autonomous tractors, autonomous navigation for such under canopy robots remains an open challenge because Global Navigation Satellite System (GNSS) is unreliable under the plant canopy. We present a hybrid navigation system that autonomously switches between different sets of sensing modalities to enable full field navigation, both inside and outside of crop. By choosing the appropriate path reference source, the robot can accommodate for loss of GNSS signal quality and leverage row-crop structure to autonomously navigate. However, such switching can be tricky and difficult to execute over scale. Our system provides a solution by automatically switching between an exteroceptive sensing based system, such as Light Detection And Ranging (LiDAR) row-following navigation and waypoints path tracking. In addition, we show how our system can detect when the navigate fails and recover automatically extending the autonomous time and mitigating the necessity of human intervention. Our system shows an improvement of about 750 m per intervention over GNSS-based navigation and 500 m over row following navigation.
UR - http://www.scopus.com/inward/record.url?scp=85168688304&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85168688304&partnerID=8YFLogxK
U2 - 10.1109/ICRA48891.2023.10160990
DO - 10.1109/ICRA48891.2023.10160990
M3 - Conference contribution
AN - SCOPUS:85168688304
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 11824
EP - 11830
BT - Proceedings - ICRA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 May 2023 through 2 June 2023
ER -