Papers

4

Total Citations

87

H-Index

2

About

Jonatha Rodrigues da Costa is a robotics researcher whose work focuses on the intersection of trajectory planning, system identification, and control for industrial manipulators. His most impactful contributions address two critical challenges in robotics: efficient motion planning and accurate system modeling. In his highly cited 2020 work, Costa pioneered the use of artificial potential fields combined with metaheuristic algorithms for trajectory planning, offering a novel solution to reduce robot downtime and improve production efficiency—a paper that has garnered 42 citations. His 2021 study, with 41 citations, introduced the Recursive Least Squares with Kalman Filter (RLS-KF) method for identifying robotic manipulator dynamics, significantly enhancing model accuracy for control applications. Costa also explores machine learning techniques for nonlinear system identification, as seen in his 2019 work on robotic arm modeling. His research extends to dynamic modeling and controller design, including PID and LQR implementations for cylindrical manipulators. Through these contributions, Costa is advancing the precision and reliability of industrial robotics, making his work essential reading for researchers in automation, control systems, and intelligent manufacturing.

Research Focus

Key Achievements

2
H-Index
4
Papers
87
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Trajectory Planning Using Artificial Potential Fields with Metaheuristics
42 citations · 2020
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Universidade Federal do Ceará, Instituto Federal de Educação, Ciência e Tecnologia do Ceará

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago