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Showman, Robert D.

Publications and source records attributed to Showman, Robert D..

Parallel Processing Systems for Passive Ranging During Helicopter Flight

The complexity of rotorcraft missions involving operations close to the ground result in high pilot workload. In order to allow a pilot time to perform mission-oriented tasks, sensor-aiding and automation of some of the guidance and control functions are highly desirable. Images from an electro-optical sensor provide a covert way of detecting objects in the flight path of a low-flying helicopter. Passive ranging consists of processing a sequence of images using techniques based on optical low computation and recursive estimation. The passive ranging algorithm has to extract obstacle information from imagery at rates varying from five to thirty or more frames per second depending on the helicopter speed. We have implemented and tested the passive ranging algorithm off-line using helicopter-collected images. However, the real-time data and computation requirements of the algorithm are beyond the capability of any off-the-shelf microprocessor or digital signal processor. This paper describes the computational requirements of the algorithm and uses parallel processing technology to meet these requirements. Various issues in the selection of a parallel processing architecture are discussed and four different computer architectures are evaluated regarding their suitability to process the algorithm in real-time. Based on this evaluation, we conclude that real-time passive ranging is a realistic goal and can be achieved with a short time.

Sridhar, Bavavar

Model Based Vision for Aircraft Position Determination

This paper investigates the use of imaging sensors to estimate the position of an aircraft with respect to the runway during landing. Passive vision techniques to estimate aircraft position during landing rely on the known runway model, images acquired by onboard imaging sensor, orientation information provided by the inertial navigation system and the position estimate provided by devices such as the global positioning system. Point features in the runway model are compared with the onboard sensor images of the features and the difference between the two is used to correct the aircraft position and orientation. In this paper the sensitivity of point features is examined as a means of determining the accuracy of such position estimation techniques. Expressions are derived for the sensitivity of image point to errors in the position and orientation of the sensor. Using these, the sensitivity of the image to aircraft position and orientation errors along a typical landing glide path is studied. A least squares technique based on this sensitivity analysis is described for the correction of position and orientation estimates. The final version of the paper will include results from the application of this analysis to real image sequences collected in flight.

Sridhar, Banavar

Vertical Axis Rotational Motion Cues in Hovering Flight Simulation

A previous study that examined how yaw motion affected a pilot's ability to perform realistic hovering flight tasks indicated that any amount of pure yaw motion had little-to-no effect on pilot performance or opinion. In that experiment, pilots were located at the vehicle's center of rotation; thus lateral or longitudinal accelerations were absent. The purpose of the new study described here was to investigate further these unanticipated results for additional flight tasks, but with the introduction of linear accelerations associated with yaw rotations when the pilot is not at the center of rotation. The question of whether a yaw motion degree-of-freedom is necessary or not is important to government regulators who specify what simulator motions are necessary according to prescribed levels of simulator sophistication. Currently, specifies two levels of motion sophistication for flight simulators: full 6-degree-of-freedom and 3-degree-of-freedom. For the less sophisticated simulator, the assumed three degrees of freedom are pitch, roll, and heave. If other degrees of freedom are selected, which are different f rom these three, they must be qualified on a case-by-case basis. Picking the assumed three axes is reasonable and based upon experience, but little empirical data are available to support the selection of critical axes. Thus, the research described here is aimed at answering this question. The yaw and lateral degrees of freedom were selected to be examined first, and maneuvers were defined to uncouple these motions from changes in the gravity vector with respect to the pilot. This approach simplifies the problem to be examined. For this experiment, the NASA Ames Vertical Motion Simulator was used in a comprehensive investigation. The math model was an AH-64 Apache in hover, which was identified from flight test data and had previously been validated by several AH-64 pilots. The pilot's head was located 4.5 ft in front of the vehicle center of gravity, which is representative of the AH-64 pilot location. Six test pilots flew three tasks that were specifically designed to represent a broad class of situations in which both lateral and yaw motion cues may be useful. For the first task, the pilot controlled only the yaw axis and was required to rapidly acquire a North heading from 15 deg yaw offsets to either the East or West. This task allowed for full, or 1:1, motion to be used in all axes (yaw, lateral, and longitudinal). The second task was a 10 sec., 180 deg. pedal turn over a runway, but with the pilot only controlling the yaw degree-of-freedom. The position of the vehicle's center-of-mass remained fixed. This maneuver was taken from a current U.S. Army rotary wing design standard5 and is representative of a maneuver performed for acceptance of military helicopters; however, it does not allow for full 1:1 motion, since the simulator cab cannot rotate 180 deg. The third task required the pilot to perform a rapid 9 ft climb at a constant heading. This task was challenging, because rapid collective lever movement in the unaugmented AH64 results in a substantial yawing moment (due to engine torque) that must be countered by the pilot. This task also had full motion in all axes, but, in this case, the pilot had two axes to control simultaneously, rather than one as in the previous tasks. Four motion configurations were examined for each task: full motion (except for the 180 deg turn, for which the motion system was configured to provide as much motion as possible), full linear with no yaw motion, full yaw with no linear motion, and no motion. Each configuration was flown four times in a randomized test matrix, and the pilots were not informed of the configuration given. Vehicle state data were recorded for objective performance comparisons, and pilots provided subjective comments and ratings. As part of the pilots' evaluation, they were asked to rate the compensation required, the overall fidelity of the motion as compared to real flight, and whether motion was detected or not in each of the six degrees of freedom. In addition, the pilots provided a numerical level-of confidence rating, between 1 and 7, corresponding to how sure they were whether or not motion was present in each degree-of-freedom. The latter rating allow classical signal detection analysis to be performed.

Schroeder, Jeffrey A.