Robot behavior and distance estimation in indoorgml maps using combinatorial and sampling-based planning approaches

Abstract

From the past few years, the importance of behavior-based robots and Indoor
navigation system is extremely increased to its tracking and wayfinding under
the consideration of making the presence of robot behavior in different fields of
social interest. In a behavior-based system, the basic strategy the overall
behavior tasks are divided into smaller independent behaviors that focus on the
execution of particular tasks such as the behavior of a robot for Indoor
environment one behavior can focus on the wall following while the other one
focuses on obstacle avoidance etc. Indoor navigation turns an essential concern
presently because almost a lot of people spend more time in the Indoor
environment. It becomes a very essential thought in different fields such as
hospitals, transportation, marketing, and military purpose. In this paper, we
describe some behaviors of a robot and two basic distance estimation approaches
such as combinatorial planning and sampling-based planning, these two
planning techniques are the concepts of motion planning. For finding the path
over the continuous configuration space without restoring to approximations
combinatorial planning is used for that. Sampling-based planning is the most
used concept in planning, it offers a successful solution in wayfinding of path
planning and because of this it’s performed in various fields of robotics.
Therefore, we apply combinatorial and sampling-based approaches for distance
estimation in IndoorGML maps.