Manuel Simas
Papers
1
Total Citations
4
H-Index
1
About
Manuel Simas is a robotics researcher whose work focuses on the critical challenge of enabling autonomous aerial robots to navigate safely in dynamic, real-world environments. His primary research areas include simultaneous localization and mapping (SLAM), moving object tracking, and sensor fusion for unmanned aerial vehicles (UAVs). Simas’s major contribution lies in the development of an Extended Kalman Filter (EKF) for SLAM with Moving Objects Tracking (SLAMMOT), a framework that allows a UAV to simultaneously map its surroundings, localize itself, and track moving obstacles—a key capability for applications like search-and-rescue or warehouse inspection. His most cited work, "Preliminary Results on 2-D Simultaneous Localization and Mapping for Aerial Robots in Dynamic Environments" (2019), with 4 citations, demonstrates a practical validation of this approach, addressing the often-overlooked problem of uncertainty in cluttered spaces. While still early in his career, Simas’s research lays important groundwork for more resilient autonomous flight, bridging the gap between static mapping and truly responsive navigation.
Research Focus
Key Achievements
Top Papers
- 1