Development of sensor system for autonomous quadcopter cartographer

Abstract

Research into autonomous navigation of Micro-Aerial Vehicles (MAVs) has become increasingly popular in recent years. Outdoor autonomous features are largely reliant on GPS technology to estimate their position, velocity and orientation. However, the same method cannot be used for indoor environments, because of the lack of GPS signals. This project, carried out by three people in a team, aims to design and create a quadcopter that will be able to perform autonomous SLAM and exploration algorithms using an on-board computer, while maintaining a small footprint and carry a minimal set of sensory equipment. The scope of this report consists of an overview of SLAM and self-exploration methods used in indoor GPS-denied environments, as well as the development and implementation of a quadcopter platform that uses a LIDAR sensor for navigation. Other aspects of the project that are briefly mentioned in this report include an investigation of the effect and feasibility of creating a ducted frame for improved thrust, and an implementation of autonomous control frameworks for collision avoidance and position control.