Mostafa Sharifi

University of Canterbury, Semnan University, AgResearch

Papers

7

Total Citations

118

H-Index

6

About

Mostafa Sharifi is a leading researcher in agricultural robotics and autonomous navigation, specializing in mechatronic design and vision-based control for mobile robots operating in complex, unstructured environments. His major contributions center on developing innovative navigation and path planning algorithms that enable robots to function reliably in orchards, pastures, and GPS-denied outdoor settings. Notably, his highly cited work on a novel vision-based row guidance approach (37 citations) introduced a graph partitioning technique for robust crop-row following, while his random particle optimization algorithm (28 citations) advanced real-time path planning in dynamic environments. Sharifi also led the mechatronic design of MARIO, a non-holonomic omnidirectional robot for primary production (19 citations), demonstrating an integrated CAD/CAM/CAE approach. His research extends to LiDAR-based pasture biomass measurement and visual odometry for pose estimation, showcasing his versatility in sensor fusion. With a growing citation impact, Sharifi’s work is foundational for the next generation of intelligent agricultural robots, bridging the gap between theoretical algorithms and practical field deployment.

Research Focus

Key Achievements

6
H-Index
7
Papers
118
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
A novel vision based row guidance approach for navigation of agricultural mobile robots in orchards
37 citations · 2015
📈 Most Prolific Year: 2015 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: University of Canterbury, Semnan University, AgResearch

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago