Alejandro Olivas
Papers
1
Total Citations
2
H-Index
1
About
Alejandro Olivas is a mobile robotics researcher whose work focuses on enabling safe autonomous navigation in unstructured environments. His primary research areas include 3D point cloud processing, obstacle detection, and real-time environmental perception for mobile robots. Olivas made a significant contribution with his paper "Obstacle Detection with Differences of Normals in Unorganized Point Clouds for Mobile Robotics" (2023), which introduces a novel algorithm that leverages differences of normals to identify obstacles in unorganized point cloud data—a critical capability for robots operating in unpredictable, real-world settings. This work addresses the pressing need for accurate, real-time environmental analysis to ensure safe path planning and robot operation. While his citation count is currently modest (2 citations), the paper represents an important step forward in practical, computationally efficient perception for field robotics. Olivas's research is particularly relevant for applications in search-and-rescue, agricultural robotics, and autonomous exploration, where traditional structured environments cannot be assumed. His work continues to push the boundaries of how robots perceive and navigate complex, unstructured terrain.
Research Focus
Key Achievements
Top Papers
- 1