Autonomous Navigation of UAV through GPS-Denied Indoor Environment with Obstacles

Abstract

The autonomous navigation of an Unmanned Aerial Vehicle (UAV) around obstacles in an indoor environment is a challenging task. The challenges arise from a number of factors including localization and mapping, and path planning for navigation to the goal position while avoiding collisions using limited knowledge about the environment generated from on-board sensors. Moreover, the environment in which the UAV ies poses many constraints over the type of sensors and the kind of algorithms employed for the localization and path planning. For example, infrared proximity sensors are not suitable for outdoor use due to ambient infrared radiation. Similarly, in indoor environments, GPS is not available for localization and cameras cannot be eectively used in low/varying lighting conditions. This paper suggests and simulates a quad-copter UAV system equipped with inertial and sonar sensors to enable autonomous ight in a GPS-denied indoor environment with obstacles. The UAV can autonomously navigate around the obstacles to the target without the need of any user interaction. The performance of the UAV platform alongwith the software algorithms developed for navigation and control is tested with the help of a realistic simulation environment designed in Matlab. The simulation uses quad-copter dynamical equations for motion simulation and detailed sensor models for simulation of sensor data.