Multi-Sensor Localization and Navigation for Remote Manipulation in Smoky Areas

Abstract

Abstract When localizing mobile sensors and actuators in

indoor environments laser meters, ultrasonic meters or

even image processing techniques are usually used. On

the other hand, in smoky conditions, due to a fire or

building collapse, once the smoke or dust density grows,

optical methods are not efficient anymore. In these

scenarios other type of sensors must be used, such as

sonar, radar or radiofrequency signals. Indoor

localization in low‐visibility conditions due to smoke is

one of the EU GUARDIANS [1] project goals.

The developed method aims to position a robot in front

of doors, fire extinguishers and other points of interest

with enough accuracy to allow a human operator to

manipulate the robot’s arm in order to actuate over the

element. In coarse‐grain localization, a fingerprinting

technique based on ZigBee and WiFi signals is used,

allowing the robot to navigate inside the building in

order to get near the point of interest that requires

manipulation. In fine‐grained localization a remotely

controlled programmable high intensity LED panel is

used, which acts as a reference to the system in smoky

conditions. Then, smoke detection and visual fine‐

grained localization are used to position the robot with

precisely in the manipulation point (e.g., doors, valves,

etc.).