Ignacio Alzugaray
Papers
6
Total Citations
82
H-Index
5
About
Ignacio Alzugaray is a robotics researcher whose work bridges perception, planning, and autonomy for aerial and manipulation systems. His primary research areas include visual-inertial simultaneous localization and mapping (SLAM), continuous-time state estimation, and multi-robot calibration. Alzugaray made significant contributions to autonomous UAV navigation, notably developing a monocular-inertial SLAM system integrated directly into a short-term path-planning loop, enabling drones to operate reliably under severe computational constraints. His work on continuous-time stereo-inertial odometry advanced the fusion of asynchronous multi-modal sensor data, offering a powerful alternative to traditional discrete-time approaches. More recently, Alzugaray has explored the intersection of robotics and foundation models, introducing Dream2Real, a framework that leverages vision-language models for zero-shot 3D object rearrangement. He also proposed a distributed method for simultaneous localization and auto-calibration in multi-robot teams using Gaussian belief propagation. With over 80 citations across his most influential papers, Alzugaray’s research has been published at top venues including ICRA and IROS, and his work on object pose estimation via neural graphics primitives (Fit-NGP) continues to push the boundaries of efficient 3D perception for robotic interaction.
Research Focus
Key Achievements
Top Papers
- 1Short-term UAV path-planning with monocular-inertial SLAM in the loop26 citations · 2017
- 2
- 3Dream2Real: Zero-Shot 3D Object Rearrangement with Vision-Language Models16 citations · 2024
- 4Continuous-Time Stereo-Inertial Odometry14 citations · 2022
- 5
- 6Fit-NGP: Fitting Object Models to Neural Graphics Primitives1 citations · 2024