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Found 4 papers, 1 papers with code
LOSS-SLAM: Lightweight Open-Set Semantic Simultaneous Localization and Mapping
Enabling robots to understand the world in terms of objects is a critical building block towards higher level autonomy.
NeuSE: Neural SE(3)-Equivariant Embedding for Consistent Spatial Understanding with Objects
We present NeuSE, a novel Neural SE(3)-Equivariant Embedding for objects, and illustrate how it supports object SLAM for consistent spatial understanding with long-term scene changes.
Robust Change Detection Based on Neural Descriptor Fields
The ability to reason about changes in the environment is crucial for robots operating over extended periods of time.
Discrete-Continuous Smoothing and Mapping
In particular, we provide a library, DC-SAM, extending existing tools for inference problems defined in terms of factor graphs to the setting of discrete-continuous models.
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