Papers

17

Total Citations

363

H-Index

12

About

Iswanto Iswanto is a prominent robotics and autonomous systems researcher whose work spans quadrotor navigation, mobile robot control, and intelligent algorithm design. His research is particularly distinguished by contributions to path planning and motion control, where he has developed and refined algorithms that enable robots to navigate complex, obstacle-filled environments in real time. His 2019 implementation of the Artificial Potential Field algorithm for quadrotor path planning (61 citations) stands as his most influential work, demonstrating practical approaches to aerial robot collision avoidance. Complementing this, his fuzzy logic-based path planning methods and PID control optimization using intelligent search algorithms have further advanced autonomous navigation capabilities. Iswanto has also made significant strides in ground robotics, pioneering kinematic modeling for four-wheel omnidirectional robots (50 citations) and applying these systems to innovative real-world challenges, including a COVID-19 aromatherapy delivery robot. His vision-based robotics research and bibliometric analysis of robotics within Industry 4.0 reflect a researcher engaged with both technical depth and broader scholarly trends. With over 280 cumulative citations across his most recognized works, Iswanto's contributions offer valuable, accessible frameworks for students and engineers advancing the frontiers of intelligent robotics.

Research Focus

Key Achievements

12
H-Index
17
Papers
363
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Artificial Potential Field Algorithm Implementation for Quadrotor Path Planning
61 citations · 2019
📈 Most Prolific Year: 2016 (6 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Muhammadiyah University of Yogyakarta, Universitas Gadjah Mada

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago