Unmanned Aircraft Systems (UAS)
As a partner in the Australian Research Centre for Aerospace Automation (ARCAA), we are developing technologies that will allow the safe, reliable, and cost-effective operation of unmanned aircraft systems (UAS - otherwise know as unmanned aerial vehicles or UAV) for scientific and civilian applications. Target applications include aerospace automation research, environmental data collection, crop monitoring, infrastructure inspection, and low-altitude atmospheric research.
Our research is enabling the automation of small rotor-craft (helicopters) which have the advantages of being highly manoeuvrable, able to hover and travel at low speed, and capable of taking off and landing almost anywhere. We maintain a strong focus on the dependability of unmanned aircraft systems as we address the challenges of pilot-less helicopter operations in unknown cluttered environments and turbulent conditions (typical of almost any outdoor application). Reliable UAS operation under such conditions requires dependable hardware and software, precise flight control, robust state estimation, obstacle avoidance, autonomous planning, reasoning and decision making, and a high-level interface to allow the mission to be specified by a non-expert operator.
Australian Research Centre for Aerospace Automation
The Australian Research Centre for Aerospace Automation (ARCAA) is a Joint Venture between CSIRO and Queensland University of Technology (QUT) which aims to:
- develop technically enhanced UAS, focusing in particular on the research and development of automated sensing, control, and navigation systems;
- provide a research and development focus on removing the impediments to routine civilian operations of UAS;
- promote and encourage domestic and international collaborations in UAS research and development projects; and
- provide training for researchers in UAS technology.
Smart Skies
Under the auspices of ARCAA, the Aerial Robotics research team in the Autonomous Systems Laboratory are collaborating with researchers from Boeing Research & Technology, Boeing Research & Technology Australia, and QUT on the Smart Skies Project. This 3-year program is researching future technologies that will support the safe and efficient utilisation of airspace by both manned and unmanned aircraft.
For more on the Smart Skies project, visit: http://www.smartskies.com.au
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CSIRO's Rotary Unmanned Aircraft
Our robotic platform is based on a model helicopter which has proven reliable and popular amongst RC (remote control) aircraft enthusiasts. This gas powered helicopter has a 1.8m rotor diameter and 5kg payload capacity. We currently have four of these miniature helicopters - one of which is used as a training helicopter, and the other three to test and demonstrate control systems, autonomous operations, and specialty payloads.
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Research Topics
Situational Awareness
We are investigating the use of UAS for remote inspection of infrastructure such as powerlines, buildings, and bridges. One of the major challenges of using a unmanned aircraft for such tasks is providing it the ability to sense obstacles around it. The aircraft may be required to fly within meters of the structures it is inspecting, and to do so in a safe manner without any collisions. It must therefore be equipped with range sensing devices, and the ability to interpret the data from these sensors so that obstacles can be identified.
Small scale unmanned aircraft such as our autonomous helicopter platform have limited payload lifting ability, so the use of lightweight range sensing devices is essential. Our situational awareness research is therefore focused on using stereo vision and the latest lightweight laser scanner devices. Both of these range sensing techniques have their advantages, and we believe a combination of the two is well suited to our application.
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Path planning and obstacle avoidance
For many applications a UAS is required to fly to a goal GPS location or through a series of GPS waypoints. When flying at low altitude it is likely that there could be obstacles blocking a direct route to the goal.
In order to reach the goal in an efficient manner while circumnavigating obstacles, the UAS therefore needs to perform path planning. If the location of any obstacles is unknown when the initial path is planned, the UAS needs to sense these obstacles as it traverses the path, and update it's planned path to avoid collisions.
We use stereo vision and a scanning laser to build a 3D occupancy map of the world, where occupied voxels represent obstacles. A probabilistic roadmap path planner finds the initial path to the goal, and this is updated using the D*-lite algorithm when new obstacles are detected.
We have conducted dynamic re-planning experiments in simulation and with real sensors on our Air Vehicle Simulator (AVS) cable array robot. We will be testing this approach on our helicopter platform in the near future.
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Key Staff
Publications
- Stefan Hrabar and Gaurav Sukhatme. "Vision-Based Navigation Through Urban Canyons", Journal of Field Robotics, Volume 26, Issue 5, May 2009, pages 431 - 452.
- Paul Wu, Duncan Campbell and Torsten Merz. "On-board multi-objective mission planning for unmanned aerial vehicles". IEEE Aerospace Conference, 7-14 March 2009, Big Sky, Montana.
- Stefan E. Hrabar. "3D Path Planning and Stereo-based Obstacle Avoidance for Rotorcraft UAVs", IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 807-814, Sep. 2008.
- Stefan E. Hrabar and Gaurav S. Sukhatme. "Optimum Camera Angle for Optic Flow-Based Centering Response", IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3922 - 3927, Oct. 2006.
- Torsten Merz, Piotr Rudol, and Mariusz Wzorek. "Control System Framework for Autonomous Robots Based on Extended State Machines", 2006 International Conference on Autonomic and Autonomous Systems (ICAS 2006), 16-21 July 2006, Silicon Valley, California, USA.
- George Curran and Torsten Merz. "Research and Development into UAV Based Power Line Inspection", TechCon Asia Pacific 2006, 9-10 May 2006, Sydney, Australia.
- Stefan E. Hrabar, Peter I. Corke, Gaurav S. Sukhatme, Kane Usher, and Jonathan M. Roberts. "Combined Optic-Flow and Stereo-Based Navigation of Urban Canyons for a UAV" IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 302-309, 2005.
- Stefan E. Hrabar and Gaurav S. Sukhatme. "A Comparison of Two Camera Configurations For Optic-Flow Based Navigation of a UAV Through Urban Canyons", IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2673 - 2680, Sep 2004.
- Peter I. Corke, Stefan E. Hrabar, Ron Peterson, Daniela Rus, Srikanth Saripalli,
and Gaurav S. Sukhatme. "Autonomous Deployment and Repair of a Sensor Network
using an Unmanned Aerial Vehicle", IEEE International Conference on Robotics
and Automation, pp. 3602-3609, 2004.
