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Chatterji, G. B.

Publications and source records attributed to Chatterji, G. B..

Discrete range clustering using Monte Carlo methods

For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.

Chatterji, G. B.

Vision-based stereo ranging as an optimal control problem

The recent interest in the use of machine vision for flight vehicle guidance is motivated by the need to automate the nap-of-the-earth flight regime of helicopters. Vision-based stereo ranging problem is cast as an optimal control problem in this paper. A quadratic performance index consisting of the integral of the error between observed image irradiances and those predicted by a Pade approximation of the correspondence hypothesis is then used to define an optimization problem. The necessary conditions for optimality yield a set of linear two-point boundary-value problems. These two-point boundary-value problems are solved in feedback form using a version of the backward sweep method. Application of the ranging algorithm is illustrated using a laboratory image pair.

Menon, P. K. A.

A two-time-scale autopilot for high-performance aircraft

A two-time-scale autopilot is proposed for the Aircraft Controls Design Challenge problem. This control law uses a nonlinear aircraft model constructed from the given vehicle simulation. The vehicle model is partitioned into slow translational dynamics and fast rotational dynamics. Feedback linearization is then employed to synthesize control laws for these two-time scales. Due to the nature of the synthesis, the control law is suitable for automatic trajectory following, and also for pilot control.

Menon, P. K. A.

Passive obstacle location for rotorcraft guidance

Nap-of-the-earth flight mode is extremely demanding on the rotorcraft pilots. This fact has motivated the research in automating various components of low altitude rotorcraft flight operations. Concurrent with the development of guidance laws, efforts are under way to develop systems for locating the terrain and the obstacles using inputs from passive electrooptical sensors such as TV cameras and infrared imagers. A passive obstable location algorithm that uses image sequences from cameras undergoing translational and rotational motion is developed. The algorithm is in a general form and can operate in multicamera imaging environments. Performance results using an image sequence from an airborne camera are given.

Menon, P. K. A.

Vision-based optimal obstacle-avoidance guidance for rotorcraft

An optimal guidance scheme for vision-based obstacle avoidance is developed. The proposed approach is useful for automating low-altitude rotorcraft flight. It explicitly accounts for the discrete nature of range information available from vision-based sensors and uses a linear combination of flight time, square of the vehicle acceleration and the square of the distance to various sensed obstacles as the performance index. A sixth-order, three-degree-of-freedom nonlinear point-mass vehicle model is included in the analysis. Numerical results using a sample image sequence is given.

Menon, P. K. A.

A fast algorithm for image-based ranging

Image-based ranging has emerged as a critical issue in the low altitude operation of flight vehicles such as rotorcraft and planetary landers. These flight regimes require ranging systems for recovering the geometry of the terrain and obstacles for use with guidance algorithms. The development of a ranging equation combining image irradiance together with various order spatial partial derivatives and the vehicle motion parameters is discussed. The ranging equation is in the form of a polynomial in scene depth. Two-dimensional linear filters are then used to compute the coefficients of this polynomial to result in a fast image-based ranging algorithm. Performance of the algorithm is demonstrated using laboratory images.

Menon, P. K. A.