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This paper features a set of advanced technologies for autonomy and intelligence in advanced inspection systems of facility operations. These technologies offer a significant contribution to set a path to establish a system and an operating environment with autonomy and intelligence for inspection, monitoring and safety via gas and ambient sensors, video mining and speech recognition commands on unmanned ground vehicles and other platforms to support operational activities in the Cryogenics Test bed and other facilities and vehicles. These advanced technologies are in current development and progress and their functions and operations require guidance and formulation in conjunction with the development team(s) toward the system architecture.

Some selected segments of the ascent and the on-orbit data from the Space Shuttle flight, STS114, as well as some selected laboratory test article data have been analyzed using wavelets, power spectrum and autocorrelation function. Additionally, a simple approximate noise test was performed on these data segments to confirm the presence or absence of white noise behavior in the data. This study was initially directed at characterizing the on-orbit background against which a signature due to an impact during on-orbit operation could be identified. The laboratory data analyzed here mimic low velocity impact that the Orbiter may be subjected to during the very initial stages of ascent.

Training to operate and manage Constellation vehicles, which include a crewed spacecraft and the lunar lander, is an essential part of the Constellation program. This paper discusses the on-going preparations for a Constellation Training Facility (CxTF). CxTF will be compromised of training simulators that will be used, in part, to prepare crew and flight controllers for vehicle operations. Current training simulators are reviewed to identify and outline key CxTF elements, i.e., part-task and full-task trainers. These trainers are further discussed within the context of the Constellation missions.

The “low power-CO2 removal (LPCOR) system” is an advanced air revitalization system that is under development at NASA Ames Research Center. The LPCOR utilizes the fundamental design features of the ‘four bed molecular sieve’ (4BMS) CO2 removal technology of the International Space Station (ISS). LPCOR improves power efficiency by replacing the desiccant beds of the 4BMS with a membrane dryer and a state-of-the-art, structured adsorbent device that collectively require 25% of the thermal energy required by the 4BMS desiccant beds for regeneration. Compared to the 4BMS technology, it has the added functionality to deliver pure, compressed CO2 for oxygen recovery. The CO2 removal and recovery functions are performed in a two-stage adsorption compressor. CO2 is removed from the cabin air and partially compressed in the first stage. The second stage performs further compression and delivers the compressed CO2 to a reduction unit such as a Sabatier reactor for oxygen recovery.

The Controlled Environment Research Chamber (CERC) at the NASA Ames Research Center was created for early-on investigation of promising new technologies for life support of advanced space exploration missions. The CERC facility is being used to address the advanced technology requirements necessary to implement an integrated working and living environment for a planetary habitat. The CERC, along with a human-powered centrifuge, a planetary terrain simulator, advanced displays, and a virtual reality capability, is able to develop and demonstrate applicable technologies for future planetary exploration. There will be several robotic mechanisms performing exploration tasks external to the habitat that will be controlled through the virtual environment to provide representative workloads for the crew.

Dante II, an eight-legged walking robot developed by the Dante project, explored the active volcanic crater of Mount Spurr in July 1994. In this paper, we describe the operator interfaces and the network-based participation methods used during the Dante II mission. Both virtual environment and multi-modal operator interfaces provided mission support for supervised control of Dante II. Network-based participation methods including message communications, satellite transmission, and a World-Wide Web server enabled remote science and public interaction. We believe that these human-machine interfaces represent a significant advance in robotic technologies for exploration.

Remotely operating complex robotic mechanisms in unstructured natural environments is difficult at best. When the communications time delay is large, as for a Mars exploration rover operated from Earth, the difficulties become enormous. Conventional approaches, such as rate control of the rover actuators, are too inefficient and risky. The Intelligent Mechanisms Laboratory at the NASA Ames Research Center has developed over the past four years an architecture for operating science exploration robots in the presence of large communications time delays. The operator interface of this system is called the Virtual Environment Vehicle Interface (VEVI), and draws heavily on Virtual Environment (or Virtual Reality) technology. This paper describes the current operational version of VEVI, which we refer to as version 2.0. In this paper we will describe the VEVI design philosophy and implementation, and will describe some past examples of its use in field science exploration missions.

This paper summarizes the results to date of an on-going research program being conducted by NASA in conjunction with the FAA vertical flight program office. The goal of the program is to reduce pilot workload and increase safety for rotorcraft category A terminal area procedures. Two piloted simulations were conducted on the NASA Ames Vertical Motion Simulator to examine the benefits of optimal procedures, cockpit displays, and alternate cueing methods. Measures of performance, handling qualities ratings and pilot comments indicate that such enhancements can greatly assist a pilot in handling an engine failure in the terminal area.

The Columbia Accident Investigation Board issued a major recommendation to NASA. Prior to return to flight, NASA should develop and implement a comprehensive inspection plan to determine the structural integrity of all Reinforced Carbon-Carbon (RCC) system components. This inspection plan should take advantage of advanced non-destructive inspection technology. This paper describes a non-intrusive technology with a micro-flying robot to continuously monitor inside a space vehicle for any stress related fissures, cracks and foreign material embedded in walls, tubes etc.

This paper discussed how data mining techniques could give advantage to the robot in navigation, in terms of speed. The input of our navigation system is the sensory information collected by the robot's equipped landmark sensor and infra-red sensor, the process of the system is the proposed data mining technique, and the output of the system is the execution of the moving direction in a 2D Martian environment. The results demonstrate efficient goal-oriented navigation using data mining techniques.

A suite of cockpit navigation displays for low-visibility airport surface operations has been designed by researchers at NASA Ames Research Center following a human-centered process. This paper reports on the final research effort in this process that examined the procedural integration of these technologies into the flight deck. Using NASA Ames' high-fidelity Advanced Concepts Flight Simulator, eighteen airline crews completed fourteen low-visibility (RVR 1000′) land-and-taxi scenarios that included both nominal (i.e., hold short of intersections, route amendments) and off-nominal taxi scenarios designed to assess how pilots integrate these technologies into their procedures and operations. Recommendations for integrating datalink and cockpit displays into current and future surface operations are provided.