Information Maps: A Practical Approach to Position Dependent Parameterization

TL;DR

This paper introduces 'Information Maps', a practical method for storing and utilizing position-dependent parameters in algorithms, enhancing efficiency especially when analytical descriptions are infeasible.

Contribution

It presents a novel framework for hierarchical, static, and dynamic Information Maps to represent position-dependent characteristics efficiently.

Findings

Efficient storage and retrieval of position-dependent sensor attributes.

Hierarchical linking of multiple Information Maps.

Applicability to various algorithms with position-dependent parameters.

Abstract

In this contribution a practical approach to determine and store position dependent parameters is presented. These parameters can be obtained, among others, using experimental results or expert knowledge and are stored in 'Information Maps'. Each Information Map can be interpreted as a kind of static grid map and the framework allows to link different maps hierarchically. The Information Maps can be local or global, with static and dynamic information in it. One application of Information Maps is the representation of position dependent characteristics of a sensor. Thus, for instance, it is feasible to store arbitrary attributes of a sensor's preprocessing in an Information Map and utilize them by simply taking the map value at the current position. This procedure is much more efficient than using the attributes of the sensor itself. Some examples where and how Information Maps can be used are presented in this publication. The Information Map is meant to be a simple and practical approach to the problem of position dependent parameterization in all kind of algorithms when the analytical description is not possible or can not be implemented efficiently.