Johnny Evers

Cooperative defense within a single-pursuer, two-evader pursuit evasion differential game

This paper is motivated by a desire to develop analytical formulations for cooperative defensive strategies against predator(s).We formulate a single-pursuer, two-evader differential game with a novel cost functional. Each of the three agents are modeled as massless particles that move with constant velocity. The pursuer attempts to capture either of the evaders while minimizing its cost. Simultaneously, the evaders strive to maximize the pursuers cost. The proposed cost functional represents the increased cost to the pursuer when presented with multiple, potentially dangerous targets. It captures the effect of cooperation between the evaders. In order to solve the game, we develop the optimality conditions for the equilibrium strategies. We then integrate the resulting system of ordinary differential equations backwards in time from the terminal conditions to generate the optimal trajectories of the three agent system. The resulting trajectories display cooperative behaviors between the two evaders, which are qualitatively similar to behaviors found in predator-prey interactions in nature. Brief description of singular surfaces is also included.

Experimental Kinematics and Dynamics of Butterflies in Natural Flight

In this paper, we discuss the collection, post-processing and subsequent evaluation of flight data of butterflies, in various free flight scenarios. The flight data is obtained by means of a vision tracking system; from which estimates of the motion of different body parts, including the head, abdomen and wings are then determined. These estimates are subsequently post-processed with a view to examining the mathematical correlations that exist between motion of individual body parts of the butterfly with its overall flight trajectory. Preliminary results performing a comparison of different takeoff sequences, are then presented.

Active Control of Visual Sensor for Aerial Tracking

This paper addresses the problem of on-board estimation of the state and/or the velocity components of an unknown leader by open-loop control of a single camera installed on the follower aircraft. Unlike the conventional pan-tilt gimbal, a custom-built gimbal is assumed that permits translational movement of the camera. The only information about the unknown leader is deduced from its bearing and subtended angles in the image plane of the camera. An adaptive estimation algorithm is applied to estimate the state vector and the geometric parameters of the unknown object from visual measurements outside the flight control loop of the follower aircraft. Asymptotic convergence of the estimated parameters to the true ones is proven and shown to be independent of the flight controller. The estimated parameters can be used in the guidance law of the follower aircraft without any modifications to it. The main benefit of the proposed paradigm is in this decoupling of estimation from control.

Optical flow angular rate determination

One application of optical flow analyses is to determine the egomotion of moving bodies based on intensity variations in sequential sensor imagery. Full egomotion determination requires an estimate of the bodys translational velocity as well as the angular rates. Such calculations of the full egomotion require solving a system of nonlinear equations. However, if the assumption is made that the translational velocities can be estimated by another sensor (i.e. accelerometers), the resulting equations for the angular rate prediction become linear. This paper presents the set of equations for the determination of the angular rates and range from the spatio-temporal image gradients introduced when employing the optical flow constraint. Results of simulations show typical accuracy for the proposed approach.

Target tracking strategies for a nonlinear, flexible aircraft-inspired model

Aeroelastic wing micro aerial vehicle (MAV) concepts are being explored for military and civilian applications. However, on the whole, the issues of control of MAVs are largely unexplored. The authors seek to employ distributed parameter modeling and control theory in an effort to achieve agile flight potential of flexible, morphable wing MAV airframes. In this work, two Euler-Bernoulli beams connected to a rigid mass are used to model the heave dynamics of an aeroelastic wing MAV. A nonlinear aerodynamic lift force acts upon this multiple component structure. The focus of this paper is an effort to employ tools from linear distributed parameter control theory to gain insight into feasibly obtained wing shape, as a bridge to examining optimal wing morphing trajectories for achieving agile flight.

A Comparison of Trajectory Determination Approaches for Small UAVs

Abstract : In considering the problem of small unmanned aerial vehicle (SUAV) surveillance mission in a target rich environment, it is desirable to follow a trajectory path that maximizes targets coverage and observation time, while minimizing airframe maneuvering. Motivated by this requirement, this paper investigates the merits of multiple vehicle trajectory path schemes. Genetic Algorithms (GAs) and local optimum techniques are compared to a more conventional defined-path approach. The authors also introduce a polygon boundary reflection algorithm (PBRA) and investigate its merits.

Sensitivities & functional gains for a flexible aircraft-inspired model

Aeroelastic wing micro-autonomous aerial systems (MAAS) concepts are being explored for military and civilian applications. However, on the whole, the issues of control of MAAS are largely unexplored. Controllers designed using methods applicable to larger aircraft are unlikely to realize the agile flight potential of flexible wing MAAS airframes. In this paper, the authors use two Euler-Bernoulli beams connected to a rigid mass to model an aeroelastic wing MAAS. They employ Continuous Sensitivity Equation Methods to examine the sensitivity of the controlled state with respect to variation of the H∞ control parameter, with the primary goal being to gain insight into the flexible dynamics of the system in order to exploit the flexibility for control purposes. Further, the authors examine functional gains in order to determine optimal sensor placement while taking advantage of the flexibility of the MAAS model.

VISION-AUGMENTED GNC: PASSIVE RANGING FROM IMAGE FLOW

Knowledge of range and closing velocity is known to enhance missile guidance, improve launch envelope, and reduce miss; however, scenarios exist where the range-to-target is unknown to the weapon. This paper provides the mathematical framework and algorithm for calculating range-to-target from sequential optical (intensity only) images. Such use of additional information from imaging seekers to assist GNC falls into the general category of Vision-Augmented GNC (VA-GNC), and a brief overview of this emerging fleld is provided. It has been shown that through use of the optical ∞ow constraint (OFC), a range expression at each image pixel may be directly calculated from spatial-temporal gradients, known pixel angular location, and ownship motion. However, these optical ∞ow/gradient-based passive ranging algorithms are subject to singularities, noise, and bogus range estimates for certain image content. In this work, a local median flltering approach is applied to the raw range estimates to remove outliers before segmentation. Using this approach provides the additional beneflt of both intensity and range information for segmentation. Once segmented, the range to the target of interest is extracted and available for guidance or range-rate estimation. Finally, simulation performance results are presented using synthetic, analytically derived images for the case of a body-flxed

Nonlinear controllers for wing morphing trajectories of a heave dynamics model

A multiple component structure consisting of two Euler-Bernoulli beams connected to a rigid mass is used to model the heave dynamics of an aeroelastic wing micro air vehicle that is acted upon by a nonlinear aerodynamic lift force. In this work we consider two different strategies for designing nonlinear controllers that achieve specified wing morphing trajectories, namely (a) linearization followed by linear quadratic tracking and (b) a feedback linearization inner loop with sliding mode outer loop. We seek to analyze the relative performance of the two controllers as we note the advantages and disadvantages of each approach.

In-Flight Wing-Membrane Strain Measurements on Bats

An efficient system for high-resolution measurements of a bat wing’s membrane during flight is presented, proving the feasibility of dynamic strain measurements on bats wing membranes during flapping. Data were collected from wind tunnel wind-off flights of a Jamaican fruit bat, Artibeus jamaicensis, a nocturnal and frugivorous specie trained by Brown University team to fly back and forth in the test section. Visual image correlation was used for image post-processing providing spatial highresolution three-dimensional displacements and strains on the bat’s wing.