A Fusion Algorithm for Building Maps in Confined Environments for Mobile Robots

Abstract

Some problems associated with building map in confined environments for mobile robots are studied in this work. The uncertainties arising from specular reflection of ultrasonic sensors cannot make mobile robots recognize their surrounding environments correctly when mobile robots navigate in a confined environment. If the environment is known and unchanged, its map can be built with ultrasonic sensors in advance before navigation is performed. This map can provide reliable information about the environment when mobile robots work. A multi-layer fusion algorithm is proposed for building the map in advance. For the situation that the environment is unknown or variable, an adaptive ultrasonic sensor model is applied to build map dynamically. The experiment results indicate that the above fusion algorithms improve the performance of ultrasonic sensors.

Falcon: A False Ceiling Inspection Robot

“…Fuzzy logic was utilized to implement the PFC due to the following reasons: Fuzzy logic can be used to map the input and output space of a process using a set of linguistic rules without the knowledge of the underlying dynamics of the process model [ 24 , 25 , 26 ]. In the case of the Falcon robot, the exact dynamics of the robot are not known due to the difficulty of modeling the slippage of the robot when traversing on bumps such as runners and cables; Range sensor information inside a confined space, such as inside a false ceiling, is not accurate [ 27 , 28 ]. Thus, the proposed robot often encounters sensor inaccuracies where the decisions have to be made while coping with the sensor uncertainties.…”

“…Range sensor information inside a confined space, such as inside a false ceiling, is not accurate [ 27 , 28 ]. Thus, the proposed robot often encounters sensor inaccuracies where the decisions have to be made while coping with the sensor uncertainties.…”