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Found 5 papers, 0 papers with code
Online Semantic Exploration of Indoor Maps
In this paper we propose a method to extract an abstracted floor plan from typical grid maps using Bayesian reasoning.
Applying Rule-Based Context Knowledge to Build Abstract Semantic Maps of Indoor Environments
In this paper, we propose a generalizable method that systematically combines data driven MCMC samplingand inference using rule-based context knowledge for data abstraction.
A Generalizable Knowledge Framework for Semantic Indoor Mapping Based on Markov Logic Networks and Data Driven MCMC
In this paper, we propose a generalizable knowledge framework for data abstraction, i. e. finding compact abstract model for input data using predefined abstract terms.
Extracting Semantic Indoor Maps from Occupancy Grids
The primary challenge for any autonomous system operating in realistic, rather unconstrained scenarios is to manage the complexity and uncertainty of the real world.
Table-Top Scene Analysis Using Knowledge-Supervised MCMC
Our approach to generate scene graphs is probabilistic: Uncertainty in the object poses is addressed by a probabilistic sensor model that is embedded in a data driven MCMC process.
