Gianpaolo Conte

Vision-based unmanned aerial vehicle navigation using geo-referenced information

This paper investigates the possibility of augmenting an Unmanned Aerial Vehicle (UAV) navigation system with a passive video camera in order to cope with long-term GPS outages. The paper proposes a vision-based navigation architecture which combines inertial sensors, visual odometry, and registration of the on-board video to a geo-referenced aerial image. The vision-aided navigation system developed is capable of providing high-rate and drift-free state estimation for UAV autonomous navigation without the GPS system. Due to the use of image-to-map registration for absolute position calculation, drift-free position performance depends on the structural characteristics of the terrain. Experimental evaluation of the approach based on offline flight data is provided. In addition the architecture proposed has been implemented on-board an experimental UAV helicopter platform and tested during vision-based autonomous flights.

An Integrated UAV Navigation System Based on Aerial Image Matching

The aim of this paper is to explore the possibility of using geo-referenced satellite or aerial images to augment an Unmanned Aerial Vehicle (UAV) navigation system in case of GPS failure. A vision based navigation system which combines inertial sensors, visual odometer and registration of a UAV on-board video to a given geo-referenced aerial image has been developed and tested on real flight-test data. The experimental results show that it is possible to extract useful position information from aerial imagery even when the UAV is flying at low altitude. It is shown that such information can be used in an automated way to compensate the drift of the UAV state estimation which occurs when only inertial sensors and visual odometer are used.

Autonomous Landing of an Unmanned Helicopter based on Vision and Inertial Sensing

In this paper we propose an autonomous precision landing method for an unmanned helicopter based on an on-board visual navigation system consisting of a single pan-tilting camera, off-the-shelf com ...

Dynamic 3D path following for an autonomous helicopter

A hybrid control system for dynamic path following for an autonomous helicopter is described. The hierarchically structured system combines continuous control law execution with event-driven sta ...

Unmanned aerial vehicle-aided communications system for disaster recovery

After natural disasters such as earthquakes, floods, hurricanes, tornados and fires, providing emergency management schemes which mainly rely on communications systems is essential for rescue operations. To establish an emergency communications system during unforeseen events such as natural disasters, we propose the use of a team of unmanned aerial vehicles (UAVs). The proposed system is a post-disaster solution and can be used whenever and wherever required. Each UAV in the team has an onboard computer which runs three main subsystems responsible for end-to-end communication, formation control and autonomous navigation. The onboard computer and the low-level controller of the UAV cooperate to accomplish the objective of providing local communications infrastructure. In this study, the subsystems running on each UAV are explained and evaluated by simulation studies and field tests using an autonomous helicopter. While the simulation studies address the efficiency of the end-to-end communication subsystem, the field tests evaluate the accuracy of the navigation subsystem. The results of the field tests and the simulation studies show that the proposed system can be successfully used in case of disasters to establish an emergency communications system.

Micro Unmanned Aerial Vehicle Visual Servoing for Cooperative Indoor Exploration

Recent advances in the field of micro unmanned aerial vehicles (MAVs) make flying robots of small dimensions suitable platforms for performing advanced indoor missions. In order to achieve autonomous indoor flight a pose estimation technique is necessary. This paper presents a complete system which incorporates a vision-based pose estimation method to allow a MAV to navigate in indoor environments in cooperation with a ground robot. The pose estimation technique uses a lightweight light emitting diode (LED) cube structure as a pattern attached to a MAV. The pattern is observed by a ground robots camera which provides the flying robot with the estimate of its pose. The system is not confined to a single location and allows for cooperative exploration of unknown environments. It is suitable for performing missions of a search and rescue nature where a MAV extends the range of sensors of the ground robot. The performance of the pose estimation technique and the complete system is presented and experimental flights of a vertical take-off and landing (VTOL) MAV are described.

High Accuracy Ground Target Geo-location Using Autonomous Micro Aerial Vehicle Platforms

This paper presents a method for high accuracy ground target localization using a Micro Aerial Vehicle (MAV) equipped with a video camera sensor. The proposed method is based on a satellite or aeri ...

LINKMAV, A PROTOYPE ROTARY WING MICRO AERIAL VEHICLE

Abstract This paper provides an overview about the design of the LinkMAV rotary wing autonomous Micro Aerial Vehicle. The paper describes the flying platform, the main problems related to aerodynamics and propulsion, the onboard avionics and the flight control system, including the autonomous navigation algorithms. We also describe the sensor chosen for the MAV05 competition, held in Garmisch Partenkirchen, and a high level system and multi-modal interface providing more advanced autonomy in terms of collision free path planning and in-flight mission reconfiguration.

HDRC3 - A Distributed Hybrid Deliberative/Reactive Architecture for Unmanned Aircraft Systems

This chapter presents a distributed architecture for unmanned aircraft systems that provides full integration of both low autonomy and high autonomy. The architecture has been instantiated and used ...

In-flight Identification of the Augmented Flight Dynamics of the Rmax Unmanned Helicopter

The flight dynamics of the Yamaha RMAX unmanned helicopter has been investigated, and mapped into a six degrees of freedom mathematical model. The model has been obtained by a combined black-box system identification technique and a classic model-based parameter identification approach. In particular, the closed-loop behaviour of the built-in attitude control system has been studied, to support the decision whether to keep it as inner stabilization loop or to develop an own stability augmentation system. The flight test method and the test instrumentation are described in detail; some samples of the flight test data are compared to the model outputs as validation, and an overall assessment of the built-in stabilization system is supplied.