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Report abuseVision-based navigation | SLAM | Multi-sensor estimation | Space vehicles and robots autonomy
I'm a PhD student in Aerospace Engineering at DART Lab, Politecnico di Milano.
My research primarily focuses on visual navigation, SLAM, computer vision and multi-sensor state estimation, with particular interest in factor-graph methods and integrated navigation architectures. I primarily develop these methods for autonomous spacecraft navigation, especially for the exploration and characterization of small bodies and other poorly known environments, where no GNSS is available.
My work spans different parts of the navigation stack, from visual frontends and geometric vision to nonlinear estimation, simulation, validation and algorithm deployment.
Secondary research interests include event-based vision, machine learning for navigation and perception, and physically based rendering and sensor simulation. I usually spend considerable effort developing reusable and well designed software around these topics, beyond just writing papers.
Important! Some active research repositories remain private while the corresponding work is in development or under review for publication. Code is released publicly whenever possible, and I am open to sharing work in the context of research collaborations, projects and reviews for jobs.
There is also a number of other smaller utilities and libraries. The list above is intentionally selective and reflects the projects I currently maintain or develop most actively. This changes over time with the needs of ongoing research and software work.
Curiosity is my greatest strength. No matter the subject, I approach everything with awe and enthusiasm ✨.
“Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.”
Richard P. Feynman, letter to J. M. Szabados, 1965
Motto 🔥: “Wonder is anywhere, if you are curious enough to discover it.”
Coding-related motto 🤖: “Give me a task and I will code a SW library to automate it.”
Feel free to get in touch if you are interested in my work, curious to learn more, or considering a collaboration! 🚀
A library based on PyTorch to automate ML models development
Python 1
Forked from borglab/gtsam
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse m…
Jupyter Notebook
Collection of MATLAB/C++ general-purpose building blocks of estimators for spacecraft navigation.
MATLAB 1
A reusable C++20 library template with CMake, testing, packaging, and optional CUDA, OptiX, TensorRT, Python, MATLAB, and ROS 2 integrations: ready to evolve from a clean checkout into an installab…
CMake
Forked from SensorsINI/v2e
v2e-extended: an extended re-implementation of v2e for event streams simulation, including IEBCS and V2CE features and optimizations
Python
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