Autonomous Star Camera Calibration and Spacecraft Attitude Determination

This paper presents two methods of star camera calibration to determine camera calibrating parameters (like principal point, focal length etc) along with lens distortions (radial and decentering). First method works autonomously utilizing star coordinates in three consecutive image frames thus independent of star identification or biased attitude information. The parameters obtained in autonomous self-calibration technique helps to identify the imaged stars with the cataloged stars. Least Square based second method utilizes inertial star coordinates to determine satellite attitude and star camera parameters with lens radial distortion, both independent of each other. Camera parameters determined by the second method are more accurate than the first method of camera self calibration. Moreover, unlike most of the attitude determination algorithms where attitude of the satellite depend on the camera calibrating parameters, the second method has the advantage of computing spacecraft attitude independent of camera calibrating parameters except lens distortions (radial). Finally Kalman filter based sequential estimation scheme is employed to filter out the noise of the LS based estimation.

Algorithm for Autonomous Reorganization of Mobile Wireless Camera Sensor Networks to Improve Coverage

In this paper, sensing coverage by wireless camera-embedded sensor networks (WCSNs), a class of directional sensors is studied. The proposed work facilitates the autonomous tuning of orientation parameters and displacement of camera-sensor nodes in the bounded field of interest (FoI), where the network coverage in terms of every point in the FoI is important. The proposed work is first of its kind to study the problem of maximizing coverage of randomly deployed mobile WCSNs which exploits their mobility. We propose an algorithm uncovered region exploration algorithm (UREA-CS) that can be executed in centralized and distributed modes. Further, the work is extended for two special scenarios: 1) to suit autonomous combing operations after initial random WCSN deployments and 2) to improve the network coverage with occlusions in the FoI. The extensive simulation results show that the performance of UREA-CS is consistent, robust, and versatile to achieve maximum coverage, both in centralized and distributed modes. The centralized and distributed modes are further analyzed with respect to the computational and communicational overheads.

Shock tunnel measurements of surface pressures in shock induced separated flow field using MEMS sensor array

Characterized not just by high Mach numbers, but also high flow total enthalpies-often accompanied by dissociation and ionization of flowing gas itself-the experimental simulation of hypersonic flows requires impulse facilities like shock tunnels. However, shock tunnel simulation imposes challenges and restrictions on the flow diagnostics, not just because of the possible extreme flow conditions, but also the short run times-typically around 1 ms. The development, calibration and application of fast response MEMS sensors for surface pressure measurements in IISc hypersonic shock tunnel HST-2, with a typical test time of 600 mu s, for the complex flow field of strong (impinging) shock boundary layer interaction with separation close to the leading edge, is delineated in this paper. For Mach numbers 5.96 (total enthalpy 1.3 MJ kg(-1)) and 8.67 (total enthalpy 1.6 MJ kg(-1)), surface pressures ranging from around 200 Pa to 50 000 Pa, in various regions of the flow field, are measured using the MEMS sensors. The measurements are found to compare well with the measurements using commercial sensors. It was possible to resolve important regions of the flow field involving significant spatial gradients of pressure, with a resolution of 5 data points within 12 mm in each MEMS array, which cannot be achieved with the other commercial sensors. In particular, MEMS sensors enabled the measurement of separation pressure (at Mach 8.67) near the leading edge and the sharply varying pressure in the reattachment zone.

Fiber Bragg Grating Sensor Package for Submicron Level Displacement Measurements

In this article, the design and development of a Fiber Bragg Grating (FBG) based displacement sensor package for submicron level displacement measurements are presented. A linear shift of 12.12 nm in Bragg wavelength of the FBG sensor is obtained for a displacement of 6 mm with a calibration factor of 0.495 mu m/pm. Field trials have also been conducted by comparing the FBG displacement sensor package against a conventional dial gauge, on a five block masonry prism specimen loaded using three-point bending technique. The responses from both the sensors are in good agreement, up to the failure of the masonry prism. Furthermore, from the real-time displacement data recorded using FBG, it is possible to detect the time at which early creaks generated inside the body of the specimen which then prorogate to the surface to develop visible surface cracks; the respective load from the load cell can be obtained from the inflection (stress release point) in the displacement curve. Thus the developed FBG displacement sensor package can be used to detect failures in structures much earlier and to provide an adequate time to exercise necessary action, thereby avoiding the possible disaster.

Integrated Sensor Systems for Vessels of Opportunity, National Oceanographic Centre, Southampton, UK, October 10-12,2006 : workshop proceedings

The use of self-contained, low-maintenance sensor systems installed on commercial vessels is becoming an important monitoring and scientific tool in many regions around the world. These systems integrate data from meteorological and water quality sensors with GPS data into a data stream that is automatically transferred from ship to shore. To begin linking some of this developing expertise, the Alliance for Coastal Technologies (ACT) and the European Coastal and Ocean Observing Technology (ECOOT) organized a workshop on this topic in Southampton, United Kingdom, October 10-12, 2006. The participants included technology users, technology developers, and shipping representatives. They collaborated to identify sensors currently employed on integrated systems, users of this data, limitations associated with these systems, and ways to overcome these limitations. The group also identified additional technologies that could be employed on future systems and examined whether standard architectures and data protocols for integrated systems should be established. Participants at the workshop defined 17 different parameters currently being measured by integrated systems. They identified that diverse user groups utilize information from these systems from resource management agencies, such as the Environmental Protection Agency (EPA), to local tourism groups and educational organizations. Among the limitations identified were instrument compatibility and interoperability, data quality control and quality assurance, and sensor calibration andlor maintenance frequency. Standardization of these integrated systems was viewed to be both advantageous and disadvantageous; while participants believed that standardization could be beneficial on many levels, they also felt that users may be hesitant to purchase a suite of instruments from a single manufacturer; and that a "plug and play" system including sensors from multiple manufactures may be difficult to achieve. A priority recommendation and conclusion for the general integrated sensor system community was to provide vessel operators with real-time access to relevant data (e.g., ambient temperature and salinity to increase efficiency of water treatment systems and meteorological data for increased vessel safety and operating efficiency) for broader system value. Simplified data displays are also required for education and public outreach/awareness. Other key recommendations were to encourage the use of integrated sensor packages within observing systems such as 100s and EuroGOOS, identify additional customers of sensor system data, and publish results of previous work in peer-reviewed journals to increase agency and scientific awareness and confidence in the technology. Priority recommendations and conclusions for ACT entailed highlighting the value of integrated sensor systems for vessels of opportunity through articles in the popular press, and marine science. [PDF contains 28 pages]

Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition

Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements. In this work, we innovatively explore the effects of sensor displacement induced by both the intentional misplacement of sensors and self-placement by the user. The effects of sensor displacement are analyzed for standard activity recognition techniques, as well as for an alternate robust sensor fusion method proposed in a previous work. While classical recognition models show little tolerance to sensor displacement, the proposed method is proven to have notable capabilities to assimilate the changes introduced in the sensor position due to self-placement and provides considerable improvements for large misplacements.

Active control of sound radiated by a submarine hull in axisymmetric vibration using inertial actuators

This paper investigates the use of inertial actuators to reduce the sound radiated by a submarine hull under excitation from the propeller. The axial forces from the propeller are tonal at the blade passing frequency. The hull is modeled as a fluid-loaded cylindrical shell with ring stiffeners and equally spaced bulkheads. The cylinder is closed at each end by circular plates and conical end caps. The forces from the propeller are transmitted to the hull by a rigid foundation connected to the propeller shaft. Inertial actuators are used as the structural control inputs. The actuators are arranged in circumferential arrays and attached to the internal end plates of the hull. Two active control techniques corresponding to active vibration control and discrete structural acoustic sensing are implemented to attenuate the structural and acoustic responses of the submarine. In the latter technique, error information on the radiated sound fields is provided by a discrete structural acoustic sensor. An acoustic transfer function is defined to estimate the far field sound pressure from a single point measurement on the hull. The inertial actuators are shown to provide control forces with a magnitude large enough to reduce the sound due to hull vibration. © 2012 American Society of Mechanical Engineers.

Micro-electro-mechanical resonant tilt sensor

This paper reports a micro-electro-mechanical tilt sensor based on resonant sensing principles. The tilt sensor measures orientation by sensing the component of gravitational acceleration along a specified input axis. Design aspects of the tilt sensor are first introduced and a design trade-off between sensitivity, resolution and robustness is addressed. A prototype sensor is microfabricated in a foundry process. The sensor is characterized to validate predictive analytical and FEA models of performance. The prototype is tested over tilt angles ranging over ±90 degrees and the linearity of the sensor is found to be better than 1.4% over the tilt angle range of ±20°. The noise-limited resolution of the sensor is found to be approximately 0.00026 degrees for an integration time of 0.6 seconds. © 2012 IEEE.

Sensor graphs for guaranteed cooperative localization performance

A group of mobile robots can localize cooperatively, using relative position and absolute orientation measurements, fused through an extended Kalman filter (ekf). The topology of the graph of relative measurements is known to affect the steady-state value of the position error covariance matrix. Classes of sensor graphs are identified, for which tight bounds for the trace of the covariance matrix can be obtained based on the algebraic properties of the underlying relative measurement graph. The string and the star graph topologies are considered, and the explicit form of the eigenvalues of error covariance matrix is given. More general sensor graph topologies are considered as combinations of the string and star topologies, when additional edges are added. It is demonstrated how the addition of edges increases the trace of the steady-state value of the position error covariance matrix, and the theoretical predictions are verified through simulation analysis.

A thermopile based SOI CMOS MEMS wall shear stress sensor

In this paper we present for the first time, a novel silicon on insulator (SOI) complementary metal oxide semiconductor (CMOS) MEMS thermal wall shear stress sensor based on a tungsten hot-film and three thermopiles. These devices have been fabricated using a commercial 1 μm SOI-CMOS process followed by a deep reactive ion etch (DRIE) back-etch step to create silicon oxide membranes under the hot-film for effective thermal isolation. The sensors show an excellent repeatability of electro-thermal characteristics and can be used to measure wall shear stress in both constant current anemometric as well as calorimetric modes. The sensors have been calibrated for wall shear stress measurement of air in the range of 0-0.48 Pa using a suction type, 2-D flow wind tunnel. The calibration results show that the sensors have a higher sensitivity (up to four times) in calorimetric mode compared to anemometric mode for wall shear stress lower than 0.3 Pa. © 2013 IEEE.

Micro-electro-mechanical resonant tilt sensor with 250 nano-radian resolution

This paper reports a high-resolution frequency-output MEMS tilt sensor based on resonant sensing principles. The tilt sensor measures orientation by sensing the component of gravitational acceleration along a specified input axis. A combination of design enhancements enables significantly higher sensitivity for this device as compared to previously reported prototype sensors. The MEMS tilt sensor is calibrated on a manual tilt table over tilt angles ranging over 0-90 degrees with a relatively linear response measured in the range of ±20°(linearity error <2.3%) with a scale factor of approximately 50.06 Hz/degree. The noise-limited resolution of the sensor is found to be approximately 250 nano-radians for an integration time of 0.8 s, which is over an order of magnitude better than previously reported results [1]. © 2013 IEEE.

A novel ultra low power temperature sensor for UHF RFID tag chip

A novel ultra low power temperature sensor for UHF RFID tag chip is presented. The sensor consists of a constant pulse generator, a temperature related oscillator, a counter and a bias. Conversion of temperature to digital output is fulfilled by counting the number of the clocks of the temperature related oscillator in a constant pulse period. The sensor uses time domain comparing, where high power consumption bandgap voltage references and traditional ADCs are not needed. The sensor is realized in a standard 0.18 mu m CMOS process, and the area is only 0.2mm(2). The accuracy of the temperature sensor is +/- 1 degrees C after calibration. The power consumption of the sensor is only 0.9 mu W.

一个简单的机器人视觉引导装配实验系统

本文对视觉控制下的一个简单实验室装配系统作了介绍,讨论了系统组成、机器人控制、二维图象特征的提取、对物体自动识别、定位定向、系统标定、实现垒积木装配工作.本实验系统用的是我所研制的国内第一台示教再现机器人.

Automatically Recovering Geometry and Texture from Large Sets of Calibrated Images

Three-dimensional models which contain both geometry and texture have numerous applications such as urban planning, physical simulation, and virtual environments. A major focus of computer vision (and recently graphics) research is the automatic recovery of three-dimensional models from two-dimensional images. After many years of research this goal is yet to be achieved. Most practical modeling systems require substantial human input and unlike automatic systems are not scalable. This thesis presents a novel method for automatically recovering dense surface patches using large sets (1000's) of calibrated images taken from arbitrary positions within the scene. Physical instruments, such as Global Positioning System (GPS), inertial sensors, and inclinometers, are used to estimate the position and orientation of each image. Essentially, the problem is to find corresponding points in each of the images. Once a correspondence has been established, calculating its three-dimensional position is simply a matter of geometry. Long baseline images improve the accuracy. Short baseline images and the large number of images greatly simplifies the correspondence problem. The initial stage of the algorithm is completely local and scales linearly with the number of images. Subsequent stages are global in nature, exploit geometric constraints, and scale quadratically with the complexity of the underlying scene. We describe techniques for: 1) detecting and localizing surface patches; 2) refining camera calibration estimates and rejecting false positive surfels; and 3) grouping surface patches into surfaces and growing the surface along a two-dimensional manifold. We also discuss a method for producing high quality, textured three-dimensional models from these surfaces. Some of the most important characteristics of this approach are that it: 1) uses and refines noisy calibration estimates; 2) compensates for large variations in illumination; 3) tolerates significant soft occlusion (e.g. tree branches); and 4) associates, at a fundamental level, an estimated normal (i.e. no frontal-planar assumption) and texture with each surface patch.