🎓 Academic Profile
Ruth is an undergraduate student pursuing her degree in Mechatronics Engineering at the National Autonomous University of Mexico (UNAM). Her academic trajectory is centered on the integration of advanced computational intelligence with autonomous robotic systems, specifically targeting how robots perceive and navigate their environments.
🧠 Core Research Focus and Specialization
Ruth’s research is highly interdisciplinary, focusing on leveraging modern AI techniques to solve fundamental robotics challenges:
-
Convolutional Neural Networks (NNs): Her work involves the design, training, and deployment of deep learning models for various robotic applications. This includes exploring architectures like Convolutional Neural Networks (CNNs) for feature extraction and Recurrent Neural Networks (RNNs) for sequential data processing related to state estimation.
-
Robot Localization: Ruth specializes in developing algorithms that enable a robot to accurately determine its position and orientation within a given environment. This often involves integrating data from multiple sensors (e.g., LiDAR, cameras, IMUs) using techniques such as Simultaneous Localization and Mapping (SLAM) or Monte Carlo Localization.
-
Classical Vision: She maintains a strong foundation in traditional computer vision techniques, utilizing methods like feature detection (e.g., SIFT, SURF), image processing, and geometric transformations. This classical expertise often serves as a robust baseline or complementary tool to her deep learning approaches, ensuring system reliability and interpretability.