TY - GEN
T1 - Enhancing Precision Agriculture Through Human-in-the-Loop Planning and Control
AU - Deka, Shankar A.
AU - Phodapol, Sujet
AU - Gimenez, Andreu Matoses
AU - Fernandez-Ayala, Victor Nan
AU - Wong, Rufus
AU - Yu, Pian
AU - Tan, Xiao
AU - Dimarogonas, Dimos V.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.
AB - In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.
UR - http://www.scopus.com/inward/record.url?scp=85208265084&partnerID=8YFLogxK
U2 - 10.1109/CASE59546.2024.10711319
DO - 10.1109/CASE59546.2024.10711319
M3 - Conference article in proceedings
AN - SCOPUS:85208265084
T3 - IEEE International Conference on Automation Science and Engineering
SP - 78
EP - 83
BT - 2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024
PB - IEEE
T2 - IEEE International Conference on Automation Science and Engineering
Y2 - 28 August 2024 through 1 September 2024
ER -