Algorithms for spacecraft formation flying navigation based on wireless positioning system measurements

Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.

VISUAL-INERTIAL INTEGRATION FOR HUMAN MOTION TRACKING AND NAVIGATION IN FREE-LIVING ENVIRONMENTS

The aging population has become a burning issue for all modern societies around the world recently. There are two important issues existing now to be solved. One is how to continuously monitor the movements of those people having suffered a stroke in natural living environment for providing more valuable feedback to guide clinical interventions. The other one is how to guide those old people effectively when they are at home or inside other buildings and to make their life easier and convenient. Therefore, human motion tracking and navigation have been active research fields with the increasing number of elderly people. However, motion capture has been extremely challenging to go beyond laboratory environments and obtain accurate measurements of human physical activity especially in free-living environments, and navigation in free-living environments also poses some problems such as the denied GPS signal and the moving objects commonly presented in free-living environments. This thesis seeks to develop new technologies to enable accurate motion tracking and positioning in free-living environments. This thesis comprises three specific goals using our developed IMU board and the camera from the imaging source company: (1) to develop a robust and real-time orientation algorithm using only the measurements from IMU; (2) to develop a robust distance estimation in static free-living environments to estimate people’s position and navigate people in static free-living environments and simultaneously the scale ambiguity problem, usually appearing in the monocular camera tracking, is solved by integrating the data from the visual and inertial sensors; (3) in case of moving objects viewed by the camera existing in free-living environments, to firstly design a robust scene segmentation algorithm and then respectively estimate the motion of the vIMU system and moving objects. To achieve real-time orientation tracking, an Adaptive-Gain Orientation Filter (AGOF) is proposed in this thesis based on the basic theory of deterministic approach and frequency-based approach using only measurements from the newly developed MARG (Magnet, Angular Rate, and Gravity) sensors. To further obtain robust positioning, an adaptive frame-rate vision-aided IMU system is proposed to develop and implement fast vIMU ego-motion estimation algorithms, where the orientation is estimated in real time from MARG sensors in the first step and then used to estimate the position based on the data from visual and inertial sensors. In case of the moving objects viewed by the camera existing in free-living environments, a robust scene segmentation algorithm is firstly proposed to obtain position estimation and simultaneously the 3D motion of moving objects. Finally, corresponding simulations and experiments have been carried out.

[Navigation and robotics of the lateral skull base]

Computer-aided microscopic surgery of the lateral skull base is a rare intervention in daily practice. It is often a delicate and difficult minimally invasive intervention, since orientation between the petrous bone and the petrous bone apex is often challenging. In the case of aural atresia or tumors the normal anatomical landmarks are often absent, making orientation more difficult. Navigation support, together with imaging techniques such as CT, MR and angiography, enable the surgeon in such cases to perform the operation more accurately and, in some cases, also in a shorter time. However, there are no internationally standardised indications for navigated surgery on the lateral skull base. Miniaturised robotic systems are still in the initial validation phase.

Depiction of small veins draining into the vein of galen using preoperative 3-dimensional navigation in living patients

OBJECTIVE: The purpose of this study was to delineate the anatomy of the precentral cerebellar vein, superior vermian vein, and internal occipital vein using reconstructions of computed tomographic and magnetic resonance imaging scans with navigation software. These data were compared with previous anatomic and angiographic findings to show the resolution and accuracy of the system. METHODS: We retrospectively reviewed 100 patients with intracranial pathologies (50 computed tomographic scans with contrast and 50 magnetic resonance imaging scans with gadolinium) using a neuronavigation workstation for 3-dimensional reconstruction. Particular attention was paid to depiction of the precentral cerebellar vein, superior vermian vein, and internal occipital vein. The data were reviewed and analyzed. RESULTS: The precentral cerebellar vein, superior vermian vein, and its tributary, the supraculminate vein, were depicted in 52 (52%) patients. The internal occipital vein was delineated on 99 (49.5%) sides and joined the basal vein and vein of Galen in 39 (39.4%) and 60 (60.6%) hemispheres, respectively. Comparing these results with previous angiographic studies, the ability of the neuronavigation system for depicting these vessels is similar to that of digital subtraction angiography. CONCLUSION: This study illustrates the possibility of depicting the small vessels draining into the pineal region venous complex using 3-dimensional neuronavigation with an accuracy comparable to that of digital subtraction angiography. This tool provides important information for both surgical planning and intraoperative orientation.

Supporting Task-oriented Navigation in IDEs with Configurable HeatMaps

Mainstream IDEs generally rely on the static structure of a software project to support browsing and navigation. We propose HeatMaps, a simple but highly configurable technique to enrich the way an IDE displays the static structure of a software system with additional kinds of information. A heatmap highlights software artifacts according to various metric values, such as bright red or pale blue, to indicate their potential degree of interest. We present a prototype system that implements heatmaps, and we describe an initial study that assesses the degree to which different heatmaps effectively guide developers in navigating software.

Tackling Software Navigation Issues of the Smalltalk IDE

The IDE used in most Smalltalk dialects such as Pharo, Squeak or Cincom Smalltalk did not evolve significantly over the last years, if not to say decades. For other languages, for instance Java, the available IDEs made tremendous progress as Eclipse or NetBeans illustrate. While the Smalltalk IDE served as an exemplar for many years, other IDEs caught up or even overtook the erstwhile leader in terms of feature-richness, usability, or code navigation facilities. In this paper we first analyze the difficulty of software navigation in the Smalltalk IDE and second illustrate with concrete examples the features we added to the Smalltalk IDE to fill the gap to modern IDEs and to provide novel, improved means to navigate source space. We show that thanks to the agility and dynamics of Smalltalk, we are able to extend and enhance with reasonable effort the Smalltalk IDE to better support software navigation, program comprehension, and software maintenance in general. One such support is the integration of dynamic information into the static source views we are familiar with. Other means include easing the access to static information (for instance by better arranging important packages) or helping developers re-locating artifacts of interest (for example with a categorization system such as smart groups).

Hands-Free Navigation in Immersive Environments for the Evaluation of the Effectiveness of Indoor Navigation Systems

While navigation systems for cars are in widespread use, only recently, indoor navigation systems based on smartphone apps became technically feasible. Hence tools in order to plan and evaluate particular designs of information provision are needed. Since tests in real infrastructures are costly and environmental conditions cannot be held constant, one must resort to virtual infrastructures. This paper presents the development of an environment for the support of the design of indoor navigation systems whose center piece consists in a hands-free navigation method using the Microsoft Kinect in the four-sided Definitely Affordable Virtual Environment (DAVE). Navigation controls using the user's gestures and postures as the input to the controls are designed and implemented. The installation of expensive and bulky hardware like treadmills is avoided while still giving the user a good impression of the distance she has traveled in virtual space. An advantage in comparison to approaches using a head mounted display is that the DAVE allows the users to interact with their smartphone. Thus the effects of different indoor navigation systems can be evaluated already in the planning phase using the resulting system