Combined application of kalman filtering and correlation towards autonomous helicopter landing

Abstract

Autonomous helicopter landing is a challenging problem in the field of aerial robotics. An autonomous maneuver depends largely on two capabilities: the decision of where to land and the generation of control signals to guide the vehicle to a safe landing. Here we present a control system that enables a helicopter to land on a stationary target (landmark) on the ground. The autonomous landing control process uses visual information to control the position, height as well as the orientation of the helicopter relative to the target for a safe and accurate landing. A remote controlled helicopter is used for the landing tests. The vision system, i.e., a wireless camera is mounted on the body of the helicopter and pointing downwards. The control algorithm is designed in MATLAB which issues control signals to the remote control of the helicopter based on the actual and desired visual inputs to the computer control system. The designed strategy of control is totally dynamics free as long as the helicopter and camera hardware's are concern. The closed loop system is established through virtual feedback system having visual information. The application of Kalman filter (KF) is used for controlling the position and height of the helicopter. An individual controller is implemented for the orientation control based on the pattern-correlation of images.