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Sean L. Bowman

2 accepted papers

2020

Reactive Semantic Planning in Unexplored Semantic Environments Using Deep Perceptual Feedback

RA-L 2020

This letter presents a reactive planning system that enriches the topological representation of an environment with a tightly integrated semantic representation, achieved by incorporating and exploiting advances in deep perceptual learning and probabilistic semantic reasoning. Our architecture combi

Cited by 34Source ↗Scholar ↗
2017

Probabilistic data association for semantic SLAM

ICRA 2017poster

Traditional approaches to simultaneous localization and mapping (SLAM) rely on low-level geometric features such as points, lines, and planes. They are unable to assign semantic labels to landmarks observed in the environment. Furthermore, loop closure recognition based on low-level features is ofte…

Cited by 605Source ↗Scholar ↗