Obstacle detection and ranging sensor integration for a small unmanned aircraft system

In the last few years, Unmanned Aerial Systems (UAS) have been attracting enormous research interest, being employed in military and civilian missions (e.g. search and rescue, disaster assessment, urban traffic monitoring, 3D mapping, etc.) that would be risky or impossible for a human to perform. For autonomous or aided operations (e.g. automatic or aided landing), it is crucial to have on board an effective suite of sensors allowing navigation in unknown environments. This work performs obstacle detection and attitude estimation for a small quad-rotor by using low-cost sensors, namely, a Sonic Ranging Sensor (SRS) and an InfraRed Sensor (IRS), widely used in mobile applications for short distance measurements. Both sensors were controlled and managed by a microcontroller (Arduino Mega 2560) and synchronized at 2-Hz sampling. Attitude estimation was performed using multiple distance measurements between a solid surface (e.g. wall or ground) and the SRS/IRS sensors. A short range of 20–150 cm has been considered in order to assist the UAS landing procedure. The main objective was to integrate the SRS and IRS measurements for accurate distance and attitude estimation by means of variance minimization. Simulations and experimental results show the feasibility of low-cost sensor fusion for obstacle detection and ranging applications on a small rotary wing UAS.

[1]  Rezaul K. Begg,et al.  Ultrasonic and Infrared Sensors Performance in a Wireless Obstacle Detection System , 2013, 2013 1st International Conference on Artificial Intelligence, Modelling and Simulation.

[2]  R. Shibasaki,et al.  UAV BORNE MAPPING BY MULTI SENSOR INTEGRATION , 2008 .

[3]  Francesco Picariello,et al.  Atmosphere effects on sonar sensor model for UAS applications , 2016, IEEE Aerospace and Electronic Systems Magazine.

[4]  Luis Felipe Gonzalez,et al.  An Overview of Small Unmanned Aerial Vehicles for Air Quality Measurements: Present Applications and Future Prospectives , 2016, Sensors.

[5]  Zou Yi,et al.  Multi-ultrasonic sensor fusion for mobile robots , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[6]  Chih-Hao Chen,et al.  Design and experimental study of an ultrasonic sensor system for lateral collision avoidance at low speeds , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[7]  H. Eisenbeiss A MINI UNMANNED AERIAL VEHICLE (UAV): SYSTEM OVERVIEW AND IMAGE ACQUISITION , 2004 .

[8]  Hong Zhao,et al.  Energy Efficient Moving Target Tracking in Wireless Sensor Networks , 2016, Sensors.

[9]  B. Mustapha,et al.  Multiple sensors based obstacle detection system , 2012, 2012 4th International Conference on Intelligent and Advanced Systems (ICIAS2012).

[10]  Umberto Papa,et al.  Design of sonar sensor model for safe landing of an UAV , 2015, 2015 IEEE Metrology for Aerospace (MetroAeroSpace).

[11]  Steve Scheding,et al.  Developments and Challenges for Autonomous Unmanned Vehicles - A Compendium , 2010, Intelligent Systems Reference Library.

[12]  Girish Chowdhary,et al.  Indoor Navigation for Unmanned Aerial Vehicles , 2009 .

[13]  Reg Austin,et al.  Unmanned Aircraft Systems: Uavs Design, Development and Deployment , 2010 .