The combination of dynamic environment representations with information-gain exploration principles allows to create and maintain up-to-date models of continuously changing environments, enabling efficient and self-improving long-term operation of mobile robots.
Specifically, we demonstrate that exploiting volume information for pose estimation yields higher accuracy than relying on 2D representations with depth information.
This early classification was based on the appearance of time series and spectral representations, with little information available on generation mechanisms.
Integrating all these features across multiple exemplars into a coherent representation, as well as updating previous representations with the information provided by new exemplars, could lead to the larger frontal PSW.
The information about the building layout is extracted from the IFC file and stored in the graph representation together with information about the accessibility between spaces.
Such spatio-temporal representations provide DOTs with information on how different types of traffic signs degrade over time and further provides useful condition information necessary for predicting sign replacement plan.
For target tracking purposes it is sometimes convenient to have a slightly different representation with redundant information to facilitate and speed up the data processing.
An agent, using ADC, creates an incremental graph-based representation with the information it gathers while exploring its environment, from which common sub-graphs are identified.
The game dynamic is given by a family of N different possible differential equations (Multi-Model representation) with no information about the trajectory which is realized.
To facilitate this, we further enrich this representation with the information on the direction of the change of concentration (whether the metabolite concentration increased or decreased) and the intensity of this change.
Artifacts is another science-friendly SET that suggests using models and visual representations of information paired with guiding questions to stimulate student interest in a topic.
