Information theoretic sensor management

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 195-203).Sensor management may be defined as those stochastic control problems in which control values are selected to influence sensing parameters in order to maximize the utility of the resulting measurements for an underlying detection or estimation problem. While problems of this type can be formulated as a dynamic program, the state space of the program is in general infinite, and traditional solution techniques are inapplicable. Despite this fact, many authors have applied simple heuristics such as greedy or myopic controllers with great success. This thesis studies sensor management problems in which information theoretic quantities such as entropy are utilized to measure detection or estimation performance. The work has two emphases: Firstly, we seek performance bounds which guarantee performance of the greedy heuristic and derivatives thereof in certain classes of problems. Secondly, we seek to extend these basic heuristic controllers to nd algorithms that provide improved performance and are applicable in larger classes of problems for which the performance bounds do not apply. The primary problem of interest is multiple object tracking and identification; application areas include sensor network management and multifunction radar control.(cont.) Utilizing the property of submodularity, as proposed for related problems by different authors, we show that the greedy heuristic applied to sequential selection problems with information theoretic objectives is guaranteed to achieve at least half of the optimal reward. Tighter guarantees are obtained for diffusive problems and for problems involving discounted rewards. Online computable guarantees also provide tighter bounds in specific problems. The basic result applies to open loop selections, where all decisions are made before any observation values are received; we also show that the closed loop greedy heuristic, which utilizes observations received in the interim in its subsequent decisions, possesses the same guarantee relative to the open loop optimal, and that no such guarantee exists relative to the optimal closed loop performance. The same mathematical property is utilized to obtain an algorithm that exploits the structure of selection problems involving multiple independent objects. The algorithm involves a sequence of integer programs which provide progressively tighter upper bounds to the true optimal reward. An auxiliary problem provides progressively tighter lower bounds, which can be used to terminate when a near-optimal solution has been found.(cont.) The formulation involves an abstract resource consumption model, which allows observations that expend different amounts of available time. Finally, we present a heuristic approximation for an object tracking problem in a sensor network, which permits a direct trade-o between estimation performance and energy consumption. We approach the trade-o through a constrained optimization framework, seeking to either optimize estimation performance over a rolling horizon subject to a constraint on energy consumption, or to optimize energy consumption subject to a constraint on estimation performance. Lagrangian relaxation is used alongside a series of heuristic approximations to and a tractable solution that captures the essential structure in the problem.by Jason L. Williams.Ph.D

Autocalibrating vision guided navigation of unmanned air vehicles via tactical monocular cameras in GPS denied environments

This thesis presents a novel robotic navigation strategy by using a conventional tactical monocular camera, proving the feasibility of using a monocular camera as the sole proximity sensing, object avoidance, mapping, and path-planning mechanism to fly and navigate small to medium scale unmanned rotary-wing aircraft in an autonomous manner. The range measurement strategy is scalable, self-calibrating, indoor-outdoor capable, and has been biologically inspired by the key adaptive mechanisms for depth perception and pattern recognition found in humans and intelligent animals (particularly bats), designed to assume operations in previously unknown, GPS-denied environments. It proposes novel electronics, aircraft, aircraft systems, systems, and procedures and algorithms that come together to form airborne systems which measure absolute ranges from a monocular camera via passive photometry, mimicking that of a human-pilot like judgement. The research is intended to bridge the gap between practical GPS coverage and precision localization and mapping problem in a small aircraft. In the context of this study, several robotic platforms, airborne and ground alike, have been developed, some of which have been integrated in real-life field trials, for experimental validation. Albeit the emphasis on miniature robotic aircraft this research has been tested and found compatible with tactical vests and helmets, and it can be used to augment the reliability of many other types of proximity sensors

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen