About

Nancy Arana-Daniel is a distinguished researcher whose work sits at the intersection of robotics, computational intelligence, and control systems. Her scholarship has made substantial contributions to solving some of the most challenging problems in robotic motion and manipulation, particularly the inverse kinematics problem — a notoriously complex nonlinear challenge. Through innovative applications of metaheuristic optimization techniques, including differential evolution, firefly algorithms, and soft computing approaches, her work has provided practical, structure-independent solutions for both robotic manipulators and mobile platforms, accumulating nearly 160 citations across her top two papers alone. Beyond robotics kinematics, Arana-Daniel has advanced the field of machine learning by introducing Clifford Support Vector Machines, a groundbreaking generalization of classical SVMs using geometric algebra (84 citations). Her contributions extend further into autonomous aerial vehicles, developing neural network-based PID controllers for UAV visual servoing, adaptive control systems using extended Kalman filter training, and stable teleoperation frameworks. Her work on path planning for mobile robots using particle swarm optimization and spline-based methods demonstrates a versatile research vision. Collectively, her portfolio reflects a researcher deeply committed to bridging theoretical mathematics with real-world autonomous systems engineering.

Research Focus

Key Achievements

13
H-Index
45
Papers
646
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
A soft computing approach for inverse kinematics of robot manipulators
96 citations · 2018
📈 Most Prolific Year: 2018 (8 Papers)
🤝 Key Collaborators: 32
🏛 Institutions: Universidad de Guadalajara, Laboratoire d'Informatique de Paris-Nord, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago