Vision-based detection and tracking of aerial targets for UAV collision avoidance

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved (as opposed to radar). This paper describes the development and evaluation of a vision-based collision detection algorithm suitable for fixed-wing aerial robotics. The system was evaluated using highly realistic vision data of the moments leading up to a collision. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We make use of the enormous potential of graphic processing units to achieve processing rates of 30Hz (for images of size 1024-by- 768). Currently, integration in the final platform is under way.

A gust-attenuation controller for fixed-wing UAVs during collision avoidance course

This paper presents a nonlinear gust-attenuation controller to stabilize velocities, attitudes and angular rates of a fixed-wing unmanned aerial vehicle (UAV) in the presence of wind gusts. The proposed controller aims to achieve a steady-state flight condition such that the host UAV can avoid airspace collision with other UAVs during the cruise flight. Based on the typical UAV model capturing flight aerodynamics, a nonlinear Hinf controller is developed with rapid response property in consideration of actuator constraints. Simulations are conducted for the Shadow UAV to verify performance of the proposed controller. Comparative studies with the proportional-integral derivative (PID) controllers demonstrate that the proposed controller exhibits great performance improvement in a gusty environment, making it suitable for integration into the design of flight control systems for cruise flight with safety guarantees.

Nonlinear H_infinity control of UAVs for collision avoidance in gusty environments

This paper proposes a nonlinear H_infinity controller for stabilization of velocities, attitudes and angular rates of a fixed-wing unmanned aerial vehicle (UAV) in a windy environment. The suggested controller aims to achieve a steady-state flight condition in the presence of wind gusts such that the host UAV can be maneuvered to avoid collision with other UAVs during cruise flight with safety guarantees. This paper begins with building a proper model capturing flight aerodynamics of UAVs. Then a nonlinear controller is developed with gust attenuation and rapid response properties. Simulations are conducted for the Shadow UAV to verify performance of the proposed con- troller. Comparative studies with the proportional-integral-derivative (PID) controllers demonstrate that the proposed controller exhibits great performance improvement in a gusty environment, making it suitable for integration into the design of flight control systems for cruise flight of UAVs.

Rodent Models of Conditioned Fear: Behavioral Measures of Fear and Memory

Pavlovian fear conditioning is a robust technique for examining behavioral and cellular components of fear learning and memory. In fear conditioning, the subject learns to associate a previously neutral stimulus with an inherently noxious co-stimulus. The learned association is reflected in the subjects' behavior upon subsequent re-exposure to the previously neutral stimulus or the training environment. Using fear conditioning, investigators can obtain a large amount of data that describe multiple aspects of learning and memory. In a single test, researchers can evaluate functional integrity in fear circuitry, which is both well characterized and highly conserved across species. Additionally, the availability of sensitive and reliable automated scoring software makes fear conditioning amenable to high-throughput experimentation in the rodent model; thus, this model of learning and memory is particularly useful for pharmacological and toxicological screening. Due to the conserved nature of fear circuitry across species, data from Pavlovian fear conditioning are highly translatable to human models. We describe equipment and techniques needed to perform and analyze conditioned fear data. We provide two examples of fear conditioning experiments, one in rats and one in mice, and the types of data that can be collected in a single experiment. © 2012 Springer Science+Business Media, LLC.

Potentiation of the early visual response to learned danger signals in adults and adolescents

The reinforcing effects of aversive outcomes on avoidance behaviour are well established. However, their influence on perceptual processes is less well explored, especially during the transition from adolescence to adulthood. Using electroencephalography, we examined whether learning to actively or passively avoid harm can modulate early visual responses in adolescents and adults. The task included two avoidance conditions, active and passive, where two different warning stimuli predicted the imminent, but avoidable, presentation of an aversive tone. To avoid the aversive outcome, participants had to learn to emit an action (active avoidance) for one of the warning stimuli and omit an action for the other (passive avoidance). Both adults and adolescents performed the task with a high degree of accuracy. For both adolescents and adults, increased N170 event-related potential amplitudes were found for both the active and the passive warning stimuli compared with control conditions. Moreover, the potentiation of the N170 to the warning stimuli was stable and long lasting. Developmental differences were also observed; adolescents showed greater potentiation of the N170 component to danger signals. These findings demonstrate, for the first time, that learned danger signals in an instrumental avoidance task can influence early visual sensory processes in both adults and adolescents.

The pulling power of chocolate: Effects of approach-avoidance training on approach bias and consumption

Previous research has shown that action tendencies to approach alcohol may be modified using computerized ApproacheAvoidance Task (AAT), and that this impacted on subsequent consumption. A recent paper in this journal (Becker, Jostman, Wiers, & Holland, 2015) failed to show significant training effects for food in three studies: Nor did it find effects on subsequent consumption. However, avoidance training to high calorie foods was tested against a control rather than Approach training. The present study used a more comparable paradigm to the alcohol studies. It randomly assigned 90 participants to ‘approach’ or ‘avoid’ chocolate images on the AAT, and then asked them to taste and rate chocolates. A significant interaction of condition and time showed that training to avoid chocolate resulted in faster avoidance responses to chocolate images, compared with training to approach it. Consistent with Becker et al.'s Study 3, no effect was found on amounts of chocolate consumed, although a newly published study in this journal (Schumacher, Kemps, & Tiggemann, 2016) did do so. The collective evidence does not as yet provide solid basis for the application of AAT training to reduction of problematic food consumption, although clinical trials have yet to be conducted.