Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 61-63).

An innovative prototype intelligent wheelchair was created to test novel algorithms to help disabled wheelchair users navigate through an unstructured environment. Local planning methods were selected to assist in steering. a simple, on-board expert system attempted to find a suitable trajectory that was close to the route requested but which moved away from close objects. The algorithms were weighted by the wishes of the user. If the expert system detected that the user was unsure or inconsistent, the on-board expert was given more importance in the selection of the wheelchair route. The expert system could be over-ridden by the user if the user was consistent in the use of the joystick. The prototype intelligent wheelchair could detect the environment, modify wheelchair control data and detect the wishes of the user. Decisions were made by the expert system and pre-planned responses could be activated. Autonomous operation of the prototype intelligent wheelchair was demonstrated during tests. A micro-controller was embedded into the wheelchair control path. Information was read from the joystick and new sensor system and signals were sent to the wheelchair controller. The raw sensor data were processed to improve the reliability of the range data by mapping the sensor data onto a histogram certainty grid. The intelligent wheelchair created during this work augmented the control that the disabled user of the wheelchair could provide. It was important that the expert system operated in real time in order to assist the user. There were two real time inputs; the user input and the sensors. The user indicated a speed and direction for the wheelchair. The sensors gathered information about the environment. A <i>sensor expert </i>system then analysed the sensor information and made a recommendation for a path that would prevent collisions. The data inputs sometimes conflicted. Another expert, called <i>Fuzzy Mixer</i> considered both inputs and was responsible for the final outputs to the motor controller. the <i>joystick monitor </i>expert was responsible for interpreting the wishes of the user. Variables such as the joystick position and consistency were examined by the <i>joystick monitor  </i>to assess the desired wheelchair trajectory. The prototype intelligent wheelchair was tested in the laboratory. It was self-contained which allowed realistic testing without the burden or restriction of trailing umbilical cables. Obstacles were placed in the path of the wheelchair and the response was encouraging.

International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / A strategy for addressing the complexity of problem identification and notification by autonomous telemetry monitoring software is discussed. The Extreme Ultraviolet Explorer (EUVE) satellite's science operations center (ESOC) is completing a transition to autonomous operations. Originally staffed by two people, twenty-four hours every day, the ESOC is nearing the end of a phased transition to unstaffed monitoring of the science payload health. To develop criteria for the implementation of autonomous operations we first identified and analyzed potential risk areas. These risk areas were then considered in light of a fully staffed operations model, and in several reduced staffing models. By understanding the accepted risk in the nominal, fully staffed model, we could define what criteria to use in comparing the effectiveness of reduced staff models. The state of the scientific instrument package for EUVE is evaluated by a rule-based telemetry processing software package. In the fully automated implementation, anomalous states are characterized in three tiers: critical to immediate instrument health and safety, non-critical to immediate instrument health and safety, and affecting science data only. Each state requires specific action on the part of the engineering staff, and the response time is determined by the tier. The strategy for implementing this prioritized, autonomous instrument monitoring and paging system is presented. We have experienced a variety of problems in our implementation of this strategy, many of which we have overcome. Problems addressed include: dealing with data dropouts, determining if instrument knowledge is current, reducing the number of times personnel are paged for a single problem, prohibiting redundant notification of known problems, delaying notification of problems for instrument states that do not jeopardize the immediate health of the instrument, assuring a response to problems in a timely manner by engineering staff, and communicating problems and response status among responsible personnel.

The take-off and landing of an Unmanned Aerial Vehicle (UAV) is often the most critical and accident prone portion of its mission. This potential hazard coupled with the time and resources necessary to train a remote UAV pilot makes it desirable to have autonomous take-off and landing capabilities for UAVs. However, a robust, reliable, and accurate autonomous takeoff and landing capability for fixed-wing aircraft is not an available feature in many low-cost UAV flight control systems. This thesis describes the design of an autonomous take-off and landing algorithm implemented on an existing low-cost flight control system for a small fixed wing UAV. This thesis also describes the autonomous takeoff and landing algorithm development and gives validation results from hardware in the loop simulation.

With the increasingly rapid adoption of vehicles with autonomous features, concerns over human driver and passenger safety in such vehicles have greatly increased, especially in regards to autonomous driving features such as Tesla’s Autopilot. In order to improve current

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