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Sridhar, Banavar

Publications and source records attributed to Sridhar, Banavar.

114 records · Page 7

Rotorcraft deceleration to hover using image-based guidance

Rotorcraft operating in hostile environment fly at low altitudes to minimize exposure to the defensive weapons arrayed against them. The development of intelligent guidance commands at low altitudes requires the integration of conventional guidance with the information provided by the sensor on relative position between the vehicle and local terrain or obstacles. Deceleration to hover (DTH) is one of the common maneuvers executed by a rotorcraft. The authors describe the integration of DTH guidance logic with an image-based scheme to estimate the hover point. The performance of such a system is affected by parameters of the guidance and by navigation and image processing algorithms. Results are presented on the effect of the parameters on system performance.

Sridhar, Banavar↗

Integration of active and passive sensors for obstacle avoidance

The automatic obstacle-avoidance guidance problem is studied under the operational constraints imposed by the rotorcraft nap-of-the-earth (NOE) environment. The problem is discussed for two different circumstances. The first assumes that a full range map is available, irrespective of the type of sensor being used. Two approaches are proposed to extend a two-dimensional obstacle-avoidance concept presented by Cheng (1988). The situation where only a sparse range map is available from a passive sensor is also treated. An integrated approach that augments the passive sensor with an active one is discussed, along with the problem of data fusion and how it is affected by the characteristics of NOE flight.

Cheng, Victor H. L.↗

Computer vision techniques for rotorcraft low-altitude flight

A description is given of research that applies techniques from computer vision to automation of rotorcraft navigation. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle detection approach can be used as obstacle data for the obstacle avoidance in an automataic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data, however, presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. Some comments are made on future work and how research in this area relates to the guidance of other autonomous vehicles.

Sridhar, Banavar↗

Considerations for automated nap-of-the-earth rotorcraft flight

The authors consider nap-of-the-earth (NOE) rotorcraft flight as one of the applications in which obstacle avoidance plays a key role, and investigate the prospects of automating the guidance functions of NOE flight. Based on a proposed structure for the guidance functions, obstacle detection and obstacle avoidance are identified as the two critical components requiring substantial advancement before an automating guidance system can be realized. The major sources of difficulties in developing these two components are discussed, including sensor requirements for which a systematic analysis is provided.

Cheng, Victor H. L.↗

Simulation and analysis of image-based navigation system for rotorcraft low-altitude flight

The automation of helicopter NOE flight entails the modification of nominal trajectories on the basis of the detection and location of obstacles by means of onboard sensors. This process is presently studied using a sequence of images from a passive sensor mounted at the helicopter's center of gravity and oriented with the viewing axis along the rotorcraft's longitudinal body-axis. Three different Kalman filters are used to estimate the location of an object on the ground during the course of various simulated helicopter maneuvers; two of the three filters are found to yield good object location estimates.

Sridhar, Banavar↗

Maximum likelihood identification using an array processor

Maximum likelihood estimation (MLE) is a method used to calculate the parameters of a dynamic system. It can be applied to a large class of problems and has good statistical properties. The main disadvantage of the MLE method is the amount of computation required. This paper describes how the computation time can be reduced significantly by using an array processor. The estimation of the parameters of a dynamic model of the Space Station is used as an example to evaluate the method.

Sridhar, Banavar↗