Gert F. Trommer

Dual IMU Indoor Navigation with particle filter based map-matching on a smartphone

In this paper an Indoor Navigation System with map-matching capabilities in real-time on a smart phone is presented. The basis of the system is an in-house development of an Integrated Pedestrian Navigation System, based on 2 low-cost IMUs, an electronic compass and an altimeter with a drifting navigation solution. Combining this system with an additional laser ranger and SLAM algorithms, we are able to build accurate maps of office buildings for already visited rooms in post processing. This paper presents a map matching algorithm based on a new reduced particle filter in order to use these maps later for real-time applications without an expensive laser ranger but relying only on the dual inertial system. It can be used with both, preprocessed SLAM maps or with already available maps. Finally to smooth the resulting trajectory after particle filtering we propose the use of a new “balanced bubble band smoother” allowing the trajectory to optimally match to both, map and recorded IMU data. This new approach makes it possible to do map matching online on a smart phone.

Vision-based attitude estimation for indoor navigation using Vanishing Points and lines

A novel method for vision-based indoor attitude aiding is described in this paper. A strapdown Inertial Navigation Systems (INS) with low-cost Micro-Electrical Micro-Mechanical (MEMS) sensors is augmented by a mono-camera. Line features are detected and analyzed using the concept of Vanishing Points (VPs) and Vanishing Lines (VLs). By exploiting geometrical constraints inside buildings, long-term stable attitude information is extracted. The performance of this aiding method is analyzed in turntable experiments and demonstrated in field test within an Integrated Pedestrian Navigation System (IPNS). It is shown that the proposed method effectively eliminates attitude drift in indoor environments and is real-time capable.

Comparison of Extended and Sigma-Point Kalman Filters for Tightly Coupled GPS/INS Integration

This paper adresses the fusion of GPS measurements and inertial sensor data in tightly coupled GPS/INS navigation systems. Usually, an extended Kalman lter (EKF) is applied for this task. However, as the system dynamic model as well as the pseudorange and deltarange measurement models are nonlinear, the EKF is a sub-optimal choice from a theoretical point of view, as it approximates the propagation of mean and covariance of Gaussian random vectors through these nonlinear models by a linear transformation, which is accurate to rst-order only. The sigma-point Kalman lter (SPKF) family of algorithms achieve an accurate approximation to at least second-order. Therefore, the performance of EKF and SPKF applied to tightly-coupled GPS/INS integration is compared in numerical simulations. It is found that except in specic situations without practical relevance, both approaches oer an identical performance. This indicates that the SPKF may be an option considering the design of new systems, but a modication of existing EKF-based GPS/INS systems is neither required, nor appropriate to improve their performance.

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.

Localization in industrial halls via ultra-wideband signals

In this work a study on an indoor ultra-wideband (UWB) localization system for applications in industrial buildings is presented. Industrial environments are known for beeing extremely difficult in terms of wireless communication, mainly due to the fact, that this sort of channels are characterized by high concentration of metal objects, which cause reflections, leading to strong multipath propagation. A three-dimensional model of the warehouse has been created and used for deterministic wave propagation simulations. In the simulation, the transmitter travels along a predefined route. The receiver infrastructure consists of eight antennas with known coordinates. By means of multiple simulations, the channel influence on the UWB signals has been determined. The implications of this influence, in terms of practical system design and localization accuracy, are assessed. Furthermore the influence of pulse detection methods and geometrical configurations of base-stations are investigated. The position calculation of the mobile beacon is realized using Time Difference of Arrival approach (TDoA), employing a direct solution as well as iterative methods. Eventually the accuracy of obtained results and the theoretical limit are considered based on dilution of precision (DOP) evaluations.

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.

Multi-floor map matching in indoor environments for mobile platforms

In this paper a map matching algorithm for multi floor indoor environments including guidance of a user is presented. Inertial sensor based pedestrian navigation systems are subject to drift. Maps are to eliminate that drift by matching the path to a map. In multi floor scenarios, we propose to use not only flat floor plans but also transitions like staircases as well as ladders and elevators. This is essential for an enhanced matching of a user path to a given 3D floor plan. Especially in industrial applications this is a crucial factor as also ladders and elevators exist. In contrast to other authors, this paper considers all of these objects. 3D position estimations from an Integrated Pedestrian Navigation System (IPNS) including an inertial system as well as a barometer and a magnetometer are used. Maps must be available, either from a prior Simultaneous Localization and Mapping (SLAM) survey or from facility maps. The new map representation is used to match real sensor data from the IPNS system to a map in a real time implementation. Furthermore an online guidance implementation is presented which is also based on the new 3D map representation.

Integrity monitoring for UWB/INS tightly coupled pedestrian indoor scenarios

In this paper a tightly coupled UWB/INS system for pedestrian indoor applications is presented. In indoor environments wireless signal outage and severe multipath propagation very often lead to ranging errors and make pure UWB-based localization barely possible. On the other hand inertial sensor based systems (INS) are known for their drift with time. The integration of those two systems will allow to profit from their advantages. For the sensor data fusion the tightly coupled approach and integrity monitoring are crucial factors for a robust implementation. One possibility is the Time of Arrival (ToA) approach where the user clock bias and drift are modeled and estimated in the navigation filter. The other possibility is the Time Difference of Arrival (TDoA) approach, where the range measurements are differenced totally eliminating the clock error. If user/transmitter clocks do not follow the clock drift model very well, it is better to apply the TDoA approach. For time of arrival applications, innovation based integrity monitoring is standard. However for the use of Time Difference of Arrival measurements (TDoA) in this paper an Innovation Based Integrity Monitoring (IBIM) method is presented. This is done to determine and omit all TDoA measurement combinations including the incorrect UWB receivers. This novel approach is verified in a simulation environment. A user trajectory and inertial data are provided by a custom developed pedestrian walk generator, based on real measurement data. The UWB data is generated by a wave propagation simulator for the given indoor trajectory.

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.