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A Probabilistic-Logic based Commonsense Representation Framework for Modelling Inferences with Multiple Antecedents and Varying Likelihoods
Our resulting knowledge representation framework can encode a wider variety of world knowledge and represent beliefs flexibly using grounded concepts as well as free-text phrases.
Improving Object Permanence using Agent Actions and Reasoning
Finally, we evaluate the usability of our approach in real-world applications by conducting qualitative experiments with two Universal Robots (UR5 and UR16e) in both lab and industrial settings.
Maintaining a Reliable World Model using Action-aware Perceptual Anchoring
In this paper, we present a model for action-aware perceptual anchoring that enables robots to track objects in a persistent manner.
Direct Visual-Inertial Odometry with Semi-Dense Mapping
The first one, based on Direct Sparse Odometry (DSO), is to estimate the depths of candidate points for mapping and dense visual tracking.
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