NASA Langley Research Center National Aero-Space Plane Mission simulation profile sets

To provide information on the potential for long life service of oxidation resistant carbon-carbon (ORCC) materials in the National Aero-Space Plane (NASP) airframe environment, NASP ascent, entry, and cruise trajectories were analytically flown. Temperature and pressure profiles were generated for 20 vehicle locations. Orbital (ascent and entry) and cruise profile sets from four locations are presented along with the humidity exposure and testing sequences that are being used to evaluate ORCC materials. The four profiles show peak temperatures during the ascent leg of an orbital mission of 2800, 2500, 2000, and 1700 F. These profiles bracket conditions where carbon-carbon might be used on the NASP vehicle

Model-following control for an oblique-wing aircraft

A variable-skew oblique wing offers a substantial aerodynamic performance advantage for aircraft missions that require both high efficiency in subsonic flight and supersonic dash or cruise. The most obvious characteristic of the oblique-wing concept is the asymmetry associated with wing-skew angle which results in significant aerodynamic and inertial cross-coupling between the aircraft longitudinal and lateral-directional axes. A technique for synthesizing a decoupling controller while providing the desired stability augmentation. The proposed synthesis procedure uses the cncept of explicit model following. Linear quadratic optimization techniques are used to design the linear feedback system. The effectiveness of the control laws developed in achieving the desired decoupling is illustrated for a given flight condition by application to linearized equations of motion, and also to the nonlinear equations of six degrees of freedom of motion with nonlinear aerodynamic data

A non-deterministic planner for planetary rover autonomy

Autonomy is an important feature for space systems, especially for planetary exploration rovers. Furthermore, for every rover activity, there are intrinsic uncertainties on activity duration, position of the rover, and other environment characteristics that affect each operation, like soil condition, dust on solar panels, temperature, etc.: disregarding them during planning would bring unreliable plans, that are likely to fail. In this paper, a novel, non-deterministic planning approach for autonomous planetary exploration rovers will be presented. Uncertainties in modeling the surrounding environment and in the input from sensors are integrated in the planning process in order to make the rover activity more reliable and to prevent failures. For each plan created by a planner a measure of reliability is computed and used to predict and select the safest one. The evaluation of the plan has been performed with the Dempster-Shafer Theory of Evidence, that allows to deal with both aleatory and epistemic uncertainties. Moreover the rover has been endowed with the capability of reallocating its goals. By data-fusing payload and navigation information, gathered by the rover during its mission, assigns interest values to the existing goals or generates new goals.. The fusion yields an 'interest map,' that quantifies the level of interest of each area around the rover. In this way the planner can choose the most interesting scientific objectives to be analyzed, with limited human intervention, and reallocates its goals autonomously. The novel Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning has been used for information fusion: this theory allows to deal with vague and conflicting data. Finally the paper shows some applications of the proposed approach to the generation of reliable plans. These tests demonstrate how the planner is able to generate plans that maximize at the same time reliability and the level of interest

Planning in Multiagent Expedition with Collaborative Design Networks

Abstract. DEC-POMDPs provide formal models of many cooperative multiagent problems, but their complexity is NEXP-complete in general. We investigate a sub-class of DEC-POMDPs termed multiagent expedition. A typical instance consists of an area populated by mobile agents. Agents have no prior knowledge of the area, have limited sensing and communication, and effects of their actions are uncertain. Success relies on planing actions that result in high accumulated rewards. We solve an instance of multiagent expedition based on collaborative design network, a decision theoretic multiagent graphical model. We present a number of techniques employed in knowledge representation and demonstrate the superior performance of our system in comparison to greedy agents experimentally.