Oliver Meister

Time-Differenced Carrier Phase Measurements for Tightly Coupled GPS/INS Integration

A tightly coupled GPS/INS system is characterized by the fact that pseudorange and deltarange measurements are processed in the navigation filter in order to estimate the errors of the inertial navigation solution and to calibrate the inertial measurement unit. In this paper, the usage of time differenced carrier phase measurements instead of the delta range measurements is proposed. Usually, DGPS corrections are required in order to exploit the high accuracy of the carrier phase measurements by removing the common mode errors like ionospheric errors, ephemeris errors, or satellite clock errors. Then, techniques like carrier aided smoothing or ambiguity fixing can be applied. With the approach described in this paper, DGPS corrections are not required. Additionally, a fixing of the integer ambiguities, which is especially difficult when a single frequency receiver is used, is not required either. Forming time differences of successive carrier phase measurements, the constant integer ambiguities and most of the slowly varying common mode errors are removed. These carrier phase differences do not allow for an absolute centimeter-level positioning as it can be achieved with a DGPS base station and an ambiguity fixing, but the noise in the position information is reduced and the accuracy of the velocity and attitude estimates are improved. Details of this approach are clarified and the processing of this type of measurement in the navigation filter is addressed. The improvement in performance is illustrated via hardware-in-the-loop test results and the analysis of flight test data collected with a micro aerial vehicle.

Adaptive path planning for VTOL-UAVs

This describes the development of path planning algorithms of a small unmanned four-rotor helicopter. A powerful simulation environment of the whole UAV system - including the characteristics of the important ranging sensors for collision avoidance was developed. This is essential for developing, testing, and verifying of the algorithms. Different collision avoidance strategies for VTOL-UAVs are presented. Enhancements and miniaturization will offer more powerful sensor technologies regarding size, range, and power in the future. Very promising are improvements of sensor modules and new technologies like three-dimensional LASER range-finder, PMD sensors, RADAR range-finder, and stereo camera tracking system. Because of the general high level simulation tool introduced herein they can be easily validated and tested without the need and effort of a real hardware implementation. The results showed that adaptive path planning, including collision avoidance, is already applicable on-board small UAV vehicles. With the mentioned new sensor technologies and more calculation power, further improvements like advanced collision notice and global path planning on-board small UAVs are attainable.

Development of a GPS/INS/MAG navigation system and waypoint navigator for a VTOL UAV

Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is capable of flying automatically on a predefined path the range of possible applications is widened significantly. This paper addresses the development of the integrated GPS/INS/MAG navigation system and a waypoint navigator for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off weight below 1 kg. The core of the navigation system consists of low cost inertial sensors which are continuously aided with GPS, magnetometer compass, and a barometric height information. Due to the fact, that the yaw angle becomes unobservable during hovering flight, the integration with a magnetic compass is mandatory. This integration must be robust with respect to errors caused by the terrestrial magnetic field deviation and interferences from surrounding electronic devices as well as ferrite metals. The described integration concept with a Kalman filter overcomes the problem that erroneous magnetic measurements yield to an attitude error in the roll and pitch axis. The algorithm provides long-term stable navigation information even during GPS outages which is mandatory for the flight control of the UAV. In the second part of the paper the guidance algorithms are discussed in detail. These algorithms allow the UAV to operate in a semi-autonomous mode position hold as well an complete autonomous waypoint mode. In the position hold mode the helicopter maintains its position regardless of wind disturbances which ease the pilot job during hold-and-stare missions. The autonomous waypoint navigator enable the flight outside the range of vision and beyond the range of the radio link. Flight test results of the implemented modes of operation are shown.

Adaptive path planning for a VTOL-UAV

Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is capable of flying automatically on a predefined path, the range of possible applications is widened significantly. This paper addresses the development of adaptive path planning algorithms for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off weight below 1 kg. Because of the light weight and the small size of less than 1 m makes the use of compact and efficient sensor technology as well as small computer platforms is mandatory. The path planning for the UAV is processed in different phases. The global preflight planning phase calculates an optimized trajectory in consideration of boundaries. Afterwards, during the flight phase on-board ranging sensors are used to avoid interferences with unknown obstacles. The paper shows the details of the developed algorithms and the simulation framework allowing a verification and validation of the algorithms.

Teaming of an UGV with a VTOL-UAV in urban environments

This paper focuses on the teaming of a small unmanned ground vehicle (UGV) with an unmanned micro serial vehicle (MAV) in order to improve the navigation solution of the UGV e. g. in the case of GPS loss. The image data that is acquired by the on-board camera of the MAV is processed in order to detect the UGV marked by a colored pattern. After the identification of the UGVpsilas location in an image, the location of the UGV with respect to a geo-coordinate system and its yaw angle are estimated by taking the MAVpsilas position and attitude into account. Finally, this information is processed in the system on-board the UGV to improve the navigation solution. The performances of the particular parts of the setup and also of the whole system are illustrated with experimental data.

Decomposition of line segments into corner and statistical grown line features in an EKF-SLAM framework

Robots are emerging from industrial plants toward every peoples daily life. Thus, navigation in and understanding of human related environments becomes a prerequisite for the systems of tomorrow. Most such environments can be efficiently described using line segments. However, incorporation of extent information is often difficult, as line segments are seldom observed completely and erroneous data-association may corrupt the information associated to a certain segment. To reduce such problems this paper proposes a statistically driven description of line segments. The corresponding parameters are decomposed into line and corner features, which are separately tracked through an extended Kalman filter (EKF). Information about the extent of the lines is encoded statistically. Therefore, we use a method to recursively incorporate the information gained through a time-series of measurements. Thus, the covariance matrix belonging to a line segment grows as new regions of the corresponding line are discovered. Experimental results obtained by implementation on the mobile platform ITrike show the validity of our algorithm.

Image based augmentation of an autonomous VTOL-MAV

In this paper, the development of a vision based system for a small-scale VTOL-MAV is presented. The on-board GPS/INS navigation system is augmented by further sensors in order to allow for an autonomous waypoint mode. Especially in urban environments the GPSsignal quality is disturbed by shading and multipath propagation. The investigated vision system based on algorithms analyzing the optical flow is essential to enable the helicopter to reliably hover even in these scenarios. Due to the integration of the vision based navigation information into the navigation filter, GPSsignal outages can be bridged. The necessary height above ground information is estimated from the relative altitude change given by the barometric altimeter and the optical flow.

Detection and tracking of objects in an image sequence captured by a VTOL-UAV

This paper focusses on the automated detection and tracking of moving objects in a camera sequence, that is provided by a small, electrically powered four-rotor helicopter in a hover-and-stare scenario. Two different algorithms for identifying independently moving areas are investigated and compared. The first approach bases on the previous compensation of the camera movement by estimation of homographies. Moving regions are extracted by robust background subtraction. The second approach bases on a dense optical flow field and needs no stabilization: Single points are identified that move not consistently with the background plane. These points are merged into objects by a cluster analysis algorithm. Furthermore, a strategy for tracking these objects over time is described including a Kalman filter. Due to several reasons, not every extracted area corresponds to an independently moving object and a heuristic rule set is used to sort artifacts out. Experimental results on in-flight images are presented and the performances of the developed algorithms are compared. Finally, first steps towards a geographic location of the tracked objects are described.