Miguel Zaramalilea
Papers
1
Total Citations
3
H-Index
1
About
Miguel Zaramalilea is a leading researcher in legged robotics, specializing in autonomous locomotion through unstructured environments. His work centers on probabilistic terrain analysis, where he integrates semantic criteria to enhance how robots perceive and interact with complex landscapes. Zaramalilea’s key contribution lies in developing frameworks that enable robots to not only identify obstacles and environmental features but also characterize them in detail, allowing for adaptive leg motions and navigation strategies. His most-cited paper, "Probabilistic Terrain Analysis Using Semantic Criteria for Legged Robot Locomotion" (2024), has garnered 3 citations, reflecting its early but significant impact in advancing robust, real-world robotic mobility. By bridging perception and motion planning, Zaramalilea’s research pushes the boundaries of autonomous navigation, with implications for search-and-rescue, exploration, and industrial applications. His work is a cornerstone for students and researchers aiming to build more resilient, context-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1