Paterson's representation of the environment and the economy as twin challenges leads to the illusion of equal scale.
As animals navigate the world, they store information about their surroundings to form a coherent spatial representation of the environment in memory.
In mobile robotics, feature based maps are very popular for the representation of the environment.
This suggests that the kinds of capacities that are involved in the infant's representation of the environment are not conceptual.
In other words, the mobile robot has to deal with environmental appearance change, which modifies its representation of the environment.
This paper proposes a new methodology for image-based navigation using a self-organized visual representation of the environment.
These methods rely in most cases on a volumetric representation of the environment, with adjacency and incidence relationships.
For example, by clicking on a bottle in a UI representation of the environment they can make Atlas reach out and grab the bottle in the most efficient way.
After ranking this data, we choose only the most discriminating to build a topological representation of the environment, obtained via Principal Component Analysis (PCA).
When a user and a robot share the same physical workspace the robot may need to keep an updated 3D representation of the environment.
We also comment on its validity, at an individual level and in combination with other methods, in order to build a situated representation of the environment.
