Intrepid: A Mission to Pluto

A proposal for an exploratory spacecraft mission to Pluto/Charon system was written in response to the request for proposal for an unmannned probe to pluto (RFP). The design requirements of the RFP are presented and under the guidance of these requirements, the spacecraft Intrepid was designed. The RPF requirement that was of primary importance is the minimization of cost. Also, the reduction of flight time was of extreme importance because the atmosphere of Pluto is expected to collapse close to the Year 2020. If intrepid should arrive after the collapse, the mission would be a failure; for Pluto would be only a solid rock of ice. The topics presented include: (1) scientific instrumentation; (2) mission management, planning, and costing; (3) power and propulsion subsystem; (4) structural subsystem; (5) command, control, and communications; and (6) attitude and articulation control

SUAVE: Integrating UAV video using a 3D model

Controlling an unmanned aerial vehicle (UAV) requires the operator to perform continuous surveillance and path planning. The operator's situation awareness degrades as an increasing number of surveillance videos must be viewed and integrated. The Picture-in-Picture display (PiP) provides a solution for integrating multiple UAV camera video by allowing the operator to view the video feed in the context of surrounding terrain. The experimental SUAVE (Simple Unmanned Aerial Vehicle Environment) display extends PiP methods by sampling imagery from the video stream to texture a 3D map of the terrain. The operator can then inspect this imagery using world in miniature (WIM) or fly-through methods. We investigate the properties and advantages of SUAVE in the context of a search mission with 3 UAVs

A Hardware-in-the-Loop Simulator for Software Development for a Mars Airplane

Draper Laboratory recently developed a Hardware-In-The-Loop Simulator (HILSIM) to provide a simulation of the Aerial Regional-scale Environmental Survey (ARES) airplane executing a mission in the Martian environment. The HILSIM was used to support risk mitigation activities under the Planetary Airplane Risk Reduction (PARR) program. PARR supported NASA Langley Research Center's (LaRC) ARES proposal efforts for the Mars Scout 2011 opportunity. The HILSIM software was a successful integration of two simulation frameworks, Draper's CSIM and NASA LaRC's Langley Standard Real-Time Simulation in C++ (LaSRS++)

Navigation of a high velocity tele-operated ground vehicle through an obstacle rich environment

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1999.Includes bibliographical references (leaf 41).An experiment was designed and conducted to investigate the use of a priori overhead images in navigating an unmanned tele-operated ground vehicle through an obstacle rich environment. The obstacle courses contained many of the same types of elements that would exist in an urban setting. The corresponding a priori images depicted these obstacle courses but included some drawbacks that could be expected in an overhead image of an urban environment. For instance there were objects on the course that were not depicted on the overhead image and vice versa. The overhead images were prepared in low, medium, and high resolutions. These resolutions, one meter, half meter, and centimeter scale, were selected to be representative of what might be available in real situations. Subjects controlled the vehicle using a joystick, with reference to the a priori image and a real-time video image from the vehicle. The subjects' times to navigate the courses and their paths were recorded during the experiment. From this information, post analysis showed what types of decision errors they made on each course. Statistical analysis showed that there was no significant performance difference between the three different obstacle courses. Subjects took the longest time to navigate the courses using the low resolution overhead images, and took the shortest time with the high resolution images. There was a statistically significant difference between the average course completion time with the medium resolution map and the high resolution map. Medium and high resolution lead subjects to rely less on the video image from the vehicle. This caused them to occasionally make incorrect navigation choices. With low resolution subjects tended to use clearly discernible paths and avoid shortcuts which could have saved time. This nuance in the behavior with different resolutions underscores the importance of experimentation and suggests that further study is necessary.by Atif Iqbal Chaudhry.S.M

ISR3: Communication and Data Storage for an Unmanned Ground Vehicle*

Computer vision researchers working in mobile robotics and other real-time domains are forced to con- front issues not normally addressed in the computer vision literature. Among these are communication, or how to get data from one process to another, data storage and retrieval, primarily for transient, image- based data, and database management, for maps, ob- ject models and other permanent (typically 3D) data. This paper reviews eorts at CMU, SRI and UMass to build real-time computer vision systems for mobile robotics, and presents a new tool, called ISR3, for com- munication, data storage/retrieval and database man- agement on the UMass Mobile Perception Laboratory (MPL), a NAVLAB-like autonomous vehicle

The Effect of Level of Automation and Operator-to-Vehicle Ratio on Operator Workload and Performance in Future UAV Systems

The military intends to increase the number of UAVs in service while at the same time reducing the number of operators (Dixon, Wickens & Chang; 2004). To meet this demand, many of the current UAV operator functions will need to be automated. How automation is applied to modern systems is not fixed. Levels of automation exist along a continuum from fully manual to fully automatic. Two proposed levels of automation for future UAV systems are Management by Consent (MBC), where the operator selects the task to be executed, and Management by Exception (MBE), where the computer selects the task to be executed are. The optimum operator-to-vehicle ratio for future UAV systems is not yet known. It is expected that the optimum operator-to-vehicle ratio will vary with the level of automation applied to the system. Future systems may require the use of adaptive automation to ensure maximum human-machine performance across varying operator-to-vehicle ratios. This study aims to help determine what levels of automation are most appropriate for different operator-to-vehicle ratios and how adaptive automation should be applied in future UAV systems

A Briefing on Metrics and Risks for Autonomous Decision-Making in Aerospace Applications

Significant technology advances will enable future aerospace systems to safely and reliably make decisions autonomously, or without human interaction. The decision-making may result in actions that enable an aircraft or spacecraft in an off-nominal state or with slightly degraded components to achieve mission performance and safety goals while reducing or avoiding damage to the aircraft or spacecraft. Some key technology enablers for autonomous decision-making include: a continuous state awareness through the maturation of the prognostics health management field, novel sensor development, and the considerable gains made in computation power and data processing bandwidth versus system size. Sophisticated algorithms and physics based models coupled with these technological advances allow reliable assessment of a system, subsystem, or components. Decisions that balance mission objectives and constraints with remaining useful life predictions can be made autonomously to maintain safety requirements, optimal performance, and ensure mission objectives. This autonomous approach to decision-making will come with new risks and benefits, some of which will be examined in this paper. To start, an account of previous work to categorize or quantify autonomy in aerospace systems will be presented. In addition, a survey of perceived risks in autonomous decision-making in the context of piloted aircraft and remotely piloted or completely autonomous unmanned autonomous systems (UAS) will be presented based on interviews that were conducted with individuals from industry, academia, and government