Image Mosaicing using Cylindrical Mapping

The objective of this paper is to provide extended field of view for aerial surveillance in MAV’s. Aerial surveillance on unmanned flying vehicles using a single monocular camera is a trade-off between the level of detail obtained at low altitudes and degree of coverage obtained by flying the vehicle at high altitudes. The effective footprint of the camera is smaller if the aerial vehicle flies at higher altitudes. On the other hand, the region can be quickly searched from a higher altitude. The demand for high detail and wider coverage can be satisfied using Image Mosaicing i.e. the stitching of selected frames of a video by estimating the camera motion between the frames and thereby registering successive frames of the video to arrive at the mosaic

Leader follower formation control of ground vehicles using dynamic pixel count and inverse perspective mapping

This paper deals with leader-follower formations of non-holonomic mobile robots, introducing a formation control strategy based on pixel counts using a commercial grade electro optics camera. Localization of the leader for motions along line of sight as well as the obliquely inclined directions are considered based on pixel variation of the images by referencing to two arbitrarily designated positions in the image frames. Based on an established relationship between the displacement of the camera movement along the viewing direction and the difference in pixel counts between reference points in the images, the range and the angle estimate between the follower camera and the leader is calculated. The Inverse Perspective Transform is used to account for non linear relationship between the height of vehicle in a forward facing image and its distance from the camera. The formulation is validated with experiments

Vector field guidance for path following of MAVs in three dimensions for variable altitude maneuvers

This paper uses the vector field approach to represent both the desired ground track heading and the vertical flight path angle to navigate unmanned aerial vehicles onto the desired path. The path following is realized in 3-dimensions, thus allowing the aircraft to navigate longitudinally as well as laterally, unlike the current approaches which require the aircraft to maintain a constant altitude. This results in an increase in the maneuverability (like overflying a hill) of the vehicle allowing it to navigate over various terrains and terrain following. Methods for following straight lines in 3-dimensional space are demonstrated through numerical simulations

DUAL BEAM SYNTHESIS USING ELEMENT POSITION PERTURBATIONS AND THE G3-GA ALGORITHM

Abstract—The position perturbations of linear antenna elements are used for designing non-uniformly spaced reconfigurable antennas radiating with multiple pattern such that the same amplitude distribution and perturbed positions produces either a pencil or a flat topped beam, the difference being dependent upon phase distribution of the array. The perturbation method consists of inducing small perturbations in the element positions of a linear array to obtain the desired patterns and offer the flexibility of simple design and is similar to other adaptive techniques like phase only or phase/amplitude synthesis. The problem of finding the element position perturbations is treated as a non linear problem and has been solved using a the generalized generation gap steady state genetic algorithm (G3- GA) using parent centric crossover. In the G3-GA approach the population diversity versus selection pressure problem considers both the parent selection and the replacement plans of GA. The positionphase synthesis method using the G3-GA approach is compared with the G3-GA phase-only synthesis technique. It is seen that, an optimal set of element-perturbed positions in a constrained position range with uniform amplitude, unequally spaced elements with unequal phases has the potential to overcome the design challenge of phase only syntheses that uses a larger number of elements to get the same desired side lobe level. Further when the main beam is scanned it is found that the proposed method can maintain a sidelobe level .without distortion during beam steering for the angular positions studied

Intelligent Vision Based Unmanned Ground Vehicle Formation Control

Vehicle formation control using vision plays a vital role in the design of new control laws in order to reduce the complexity of the system. In the traditional approach, in formation control, using leader follower configuration, navigation is based on the location values transmitted by the leader. Though the method has advantages of increased range, the problems are fading, multipath reflection, Line of sight communication and the increased overhead when the number of followers increases. The present paper seeks to overcome the above problems using a simple vision based framework in real time in a leader-follower configuration. In order to reduce the processing overhead and reduce the number of sensors a simple vision based system is developed. The system consists of two parts (i) Vision system and (ii) control algorithm. The vision algorithm uses a simple color tracking mechanism .The control algorithm uses the relative distance and angular displacement between the leader and the follower. The effectiveness of the algorithms, is demonstrated for a convoy using autonomous control for the master and vision control for the follower

Novel INS/GPS Fusion Architecture for Aircraft Navigation

In this paper, we address the issue of aircraft navigational state estimation from the perspective of (i) aircraft attitude estimation, also called as the attitude heading reference system (AHRS), and (ii) estimating the full inertial solution of the aircraft (position, velocity & attitude), also known as inertial navigation system-global positioning system (INS/GPS) fusion, in the presence of accelerometer and gyroscopic bias. A suite of nonlinear filters; two Kalman filter (KF) based — extended and unscented Kalman filter (EKF, UKF) and a non-KF based filter that is the nonlinear complementary filter (NCF) on the SO(3) group, are studied and evaluated for the AHRS. In this paper we propose a novel INS/GPS fusion architecture that demonstrated a significant improvement in performance over the conventional KF based schemes, in tests done on realistic simulated aircraft data. In the proposed architecture, the attitude estimation is decoupled from the position and velocity estimation, by exploiting the NCF as it is known for its superior attitude and gyroscopic bias estimation performance. The position and velocity estimation is carried out by a conventional EKF. The crucial difference between KF based schemes and the NCF for attitude estimation is in the generation of the measurement set, which involves trigonometric inverses and are susceptible to singularities for KF based schemes, which the NCF avoids. Furthermore, the NCF algorithm is faster and computationally more efficient than a KF algorithm scheme since the NCF does not involve the computation of matrix inverses like KF based schemes