Reactive MPC for Autonomous MAV Navigation in Indoor Cluttered Environments: Flight Experiments

Abstract

This demonstrator paper describes a flight-tested, fully integrated perception-control loop for trajectory tracking with obstacle avoidance by micro-air vehicles (MAV) in indoor cluttered environments. For this purpose, a stereo-vision system is combined with an inertial measurement unit to estimate the vehicle localization and build a 3D model of the environment on-board. Emphasis is placed on a model predictive control (MPC) algorithm for safe guidance in unknown areas using the perception information. It combines an analytical linear quadratic solution for trajectory tracking and an efficient discretization strategy for collision avoidance. Experimental results in a flying arena and at an industrial site provide an overview of the demonstrator capabilities.