Papers
4
Total Citations
47
H-Index
3
About
Danial Pour Arab is an emerging researcher whose work sits at the intersection of agricultural robotics, autonomous systems, and path planning algorithms. His research has made meaningful contributions to the field of precision agriculture, particularly in developing intelligent navigation strategies for wheeled robots operating in complex field environments. Pour Arab's most recognized contribution, "Complete Coverage Path Planning for Wheeled Agricultural Robots" (2023), has accumulated 28 citations and addresses one of the central challenges in autonomous agriculture — ensuring robots can efficiently perform tasks such as harvesting, mowing, and spraying across entire field areas. Building on this foundation, his 2024 work on 3D hybrid path planning introduced a novel approach for optimizing field coverage while minimizing environmental impact, earning 14 citations in its first year. His introduction of a Row-Skip Pattern further demonstrates his drive to refine algorithmic efficiency in agricultural automation. Notably, Pour Arab's research extends beyond agriculture — his earlier work on dynamic path planning for percutaneous abdominal procedures reveals a versatile technical background spanning medical robotics. Collectively, his publications reflect a researcher committed to applying sophisticated computational methods to real-world autonomous systems, positioning him as a promising voice in the growing field of agricultural robotics and intelligent path planning.
Research Focus
Key Achievements
Top Papers
- 1Complete coverage path planning for wheeled agricultural robots28 citations · 2023
- 2
- 3
- 4