engleski

Map Building Using Autonomous Mobile Service Robots with Deep Neural Networks

The navigation of mobile (service) robots has always been an important topic in robotics, particularly for autonomous robots. In order to be able to do so a map of the area needs to be known. Here, a method for autonomous map building using Advanced Monte Carlo Localization and Deep Neural Networks is presented. The method is designed to be used in unstructured, dynamic environments, and it needs no human intervention. Method uses range data (from LIDAR, ultrasonic and other depth sensors) for recognizing patterns that are created by various obstacles, and based on deep neural network outputs, avoids obstacles while building a map of free space.

complete coverage path planning, obstacle avoidance, mobile service robots

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