Frank Dellaert
@fdellaert

Robotics & Computer Vision Professor at Georgia Tech, and part-time CAIO at Verdant Robotics. Before: stints at KUL, Skydio, Facebook B*8, Google AI.

 San Mateo, CA
cc.gatech.edu/~dellaert
Joined June 2008
220 Photos and videos
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GTSAM 4.3

After a very busy conference submission period, I was finally able to build and release GTSAM 4.3! 😃 🎉 see gtsam.org. Check out the updated website for the improvements, accompanying

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Can Jev specify graphical models for us?
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Jev + graphical models: a paradigm shift?

Could Jev + graphical models fundamentally change how we build systems that reason under uncertainty? Unless you've been off the grid this week, you now know that Jev is @typesafeai’s new model for

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Foundation Models and Hierarchical 3D Reconstruction

A special shout-out to Harneet Singh Khanuja, who just presented our paper, “Hierarchical Structure-from-Motion Scales Feedforward Reconstruction,” at the Structure-from-Motion in the Age of Deep

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FAST-Sync !

A new Georgia Institute of Technology × Northeastern University collaboration—now included with GTSAM! Shane Holmes and David Rosen at Northeastern joined Firat Taxpulat, Yiran Luo, and me at Georgia

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Bringing Geometric Foundation Models to SLAM

Dominic Maggio (@DominicMaggio1), Hyungtae Lim, and Luca Carlone from @lucacarlone1's lab at MIT are pushing an exciting direction for SLAM: bringing geometric foundation models into robotics through

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Speaking of Legged Robots

Legged robots are a great stress test for factor graphs because perception and planning both have to respect physical constraints. On June 1, I will be presenting CMC-Opt, new work by Yetong Zhang on
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Continuous-time state estimation with Gaussian processes

GTSAM now includes new tools for GP-based continuous-time state estimation, through a fabulous collaboration with Connor Holmes, Sven Lilge, Zi Cong (Daniel) Guo, and Timothy Barfoot at the University

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LP, QP, and QCQP in GTSAM

I'm happy to announce that GTSAM now supports Linear and Quadratic programming (LP and QP), *and* QCQPs in a big way. QPs are workhorses for legged locomotion and quadrotor allocation, and QCQPs open
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Awesome EqF !

@GeorgiaTech undergrads are awesome. Following last week’s post on the equivariant filter, Rohan Bansal (@rbansal22) has deployed the Awesome Equivariant Filters repo. The repo brings together a
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Factor Graphs and "World Models"

There is a lot of excitement right now around world models: learned latent-state representations that support prediction, imagination, and planning. The recent work around JEPA is especially

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