Papers

6

Total Citations

280

H-Index

6

About

Adilet Sugirbay is a leading researcher in agricultural robotics, with a focused expertise in the design and optimization of robotic apple harvesting systems. His work addresses critical challenges in precision agriculture, particularly in developing efficient, non-destructive harvesting methods. Sugirbay’s major contributions include the experimental and simulation-based analysis of optimum picking patterns, as demonstrated in his highly cited 2019 paper (74 citations), and the subsequent design and evaluation of a robotic apple harvester using those patterns (70 citations). He also pioneered the development of a simplified 4-DOF manipulator for rapid harvesting (62 citations), significantly advancing the field’s understanding of dynamic branch-stem-fruit interactions (46 citations). His comprehensive review of technological developments in robotic apple harvesters (22 citations) serves as a foundational resource for researchers. Notably, Sugirbay has also investigated fruit damage mitigation, quantifying damage factors for flexible end-effectors to improve picking performance. With over 280 total citations across his core publications, his work is instrumental in bridging simulation and real-world application, making him a key figure in the push toward fully automated, gentle, and high-speed fruit harvesting.

Research Focus

Key Achievements

6
H-Index
6
Papers
280
Total Citations
47
Avg Citations/Paper
🏆 Most Cited Paper
Experimental and simulation analysis of optimum picking patterns for robotic apple harvesting
74 citations · 2019
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: S.Seifullin Kazakh Agro Technical University, Northwest A&F University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago