Papers
8
Total Citations
239
H-Index
6
About
Erik Zamora is a leading researcher in robotics and control systems, with a focus on intelligent control, autonomous navigation, and morphological neural networks. His most impactful work, "PD Control Compensation Based on a Cascade Neural Network Applied to a Robot Manipulator" (98 citations), addresses a critical limitation of traditional PID controllers in industrial robotics—degradation of integral gain over time—by introducing a neural network-based compensation strategy that enhances stability and bandwidth. Zamora has also made significant contributions to neural network architecture, notably through his work on dendrite morphological neural networks and their training via differential evolution (56 citations), and on dendrite ellipsoidal neurons optimized with k-means (18 citations). In the field of autonomous systems, he has advanced crack recognition for building inspection using quadrotor UAVs (25 citations) and published a comprehensive survey on simultaneous localization and mapping (SLAM) for mobile robots (24 citations). His research extends to novel navigation algorithms for dynamic environments and efficient FPGA implementations for robot kinematics, demonstrating a commitment to both theoretical innovation and practical hardware solutions. With over 200 total citations, Zamora’s work continues to shape intelligent robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Recent advances on simultaneous localization and mapping for mobile robots24 citations · 2013
- 5Dendrite ellipsoidal neurons based on k-means optimization18 citations · 2018
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