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SPARKlab

SPARKlab


Sensing, Perception, Autonomy, and Robot Kinetics, cutting edge of robotics and autonomous systems research.

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What we do

✨ The SPARK Lab works at the cutting edge of robotics and autonomous systems research for air, space, and ground applications.

The lab develops the algorithmic foundations of robotics through the innovative design, rigorous analysis, and real-world testing of algorithms for single and multi-robot systems.

A major goal of the lab is to enable human-level perception, world understanding, and navigation on mobile platforms (micro aerial vehicles, self-driving vehicles, ground robots, augmented reality). Core areas of expertise include nonlinear estimation, numerical and distributed optimization, probabilistic inference, graph theory, and computer vision.


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Research highlights 🔬

Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection image missing

Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection

Semidefinite Programming (SDP) and Sums-of-Squares (SOS) relaxations have led to certifiably optimal non-minimal solvers for several robotics and computer vision problems. However, most non-minimal solvers rely on least-squares formulations, and, as a result, are brittle against outliers. While a standard approach to regain robustness against...

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3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans image missing

3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans

We present a unified representation for actionable spatial perception: 3D Dynamic Scene Graphs. Scene graphs are directed graphs where nodes represent entities in the scene (e.g. objects, walls, rooms), and edges represent relations (e.g. inclusion, adjacency) among nodes. Dynamic scene graphs (DSGs) extend this notion...

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Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping image missing

Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping

We provide an open-source C++ library for real-time metric-semantic visual-inertial Simultaneous Localization And Mapping (SLAM). The library goes beyond existing visual and visual-inertial SLAM libraries (e.g., ORB-SLAM, VINS- Mono, OKVIS, ROVIO) by enabling mesh reconstruction and semantic labeling in 3D. Kimera is designed with...

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