Christian Ascher

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.

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.

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.

Sensor data fusion in UWB-supported inertial navigation systems for indoor navigation

Indoor navigation using inertial sensors with additional radio-signal support is considered in this paper. The experimental results of data fusion between a navigation system, based on inertial measurement unit (IMU) and impulse-based UWB localization system, are presented. The IMU is additionally supported by a pedestrian step length estimations, barometer and electronic compass. The Ultra-Wideband part consists of receiver, carried by the person, and access points distributed in the scenario. The focus of the paper is put on hardware implementation and choice of the optimal data fusion technique. The presented results indicate the clear benefit of tightly coupled navigation filter, where the time differences of arrival of UWB signals are directly processed, without prior calculation of the localization solution.

Multi-sensor indoor pedestrian navigation system with vision aiding

In many indoor security and rescue missions, it is essential for the deployed personnel to have accurate positioning information available. If the scene is not explored yet, a map has to be created during the mission and exchanged between different teams, so that subsequent team members benefit from the knowledge about previously visited locations. In this paper, the multi-sensor navigation system called IndoorGuide is presented which accomplishes these tasks. It comprises two lightweight micro-electro-mechanical inertial measurement units for tracking the motion of the user. A monocular camera is integrated in the navigation system which provides attitude and position aiding. The attitude information is extracted by tracking vanishing points in the images of the camera. Position aiding is realized by mapping and recognizing visited locations. For the data fusion, a Kalman Filter and a robust optimization technique based on graphs are compared. Results from experimental test runs are presented and discussed.

Deeply Coupled GPS/INS integration in pedestrian navigation systems in weak signal conditions

This paper describes non-coherent Deeply Coupled GPS/INS integration in a pedestrian navigation system to improve position accuracy and availability in weak signal conditions. A pedestrian navigation system consists of several sensors to calculate a position of a person to guide for example rescue missions. The system presented in this paper consists of a torso mounted IMU and is used for step detection and step length and heading estimation. Additionally a barometer, magnetometer and a GPS sensor for absolute positioning are used. Since pedestrian navigation systems often are used in challenging environments like urban canyons or indoors, the use of GPS signals is often restricted. We will show that by using a Deeply Coupled GPS/INS integration system, tracking of GPS signals under weak signal conditions is possible and a seamless transition between Indoor and outdoor situations is achieved. By applying the information of a position displacement between two steps from the step length and heading estimation GPS tracking and position accuracy can be increased. For an optimal performance the system uses a deeply acquisition and re-acquisition routine. Therefore additional satellites can be used which could not have been acquired before, due to low signal to noise ratios. By carefully weighting the GPS measurements accordingly to their C / No and having a larger set of satellites available, position accuracy is increased compared to a non-vector tracking approach. The sensor fusion itself is realized in an error state space kalman filter and the step length update is performed using a state cloning technique preserving realistic position uncertainties in the filter. With this approach tracking and acquisition of GPS signals inside buildings with C / No below 20dBHz is possible. In this paper we will show that using deep integration in GPS signal tracking including step length estimations increases position accuracy of a pedestrian navigation system and availability of GPS position updates.