A behavioral-based strategy for cooperative hunting using drones is proposed in this paper. In this decentralized scheme, each drone acts as an individual agent computing its guidance strategy toward the target based on the relative position of its neighbors without the use of direct communication. The algorithm is based on the deviated pure pursuit methodology, and the emerged behavior mimics a natural hunting formation. Simulations and real-time experiments with varying conditions were carried out to validate the effectiveness of the proposed hunting scheme. Videos of the system in action can be seen on: https://youtu.be/g2dODbd6ZLA.

The question, how does an organism maintain balance? provides a unifying theme tointroduce undergraduate students to the use of mathematics and modeling techniques inbiological research. The availability of inexpensive high speed motion capture camerasmakes it possible to collect the precise and reliable data that facilitates thedevelopment of relevant mathematical models. An in–house laboratory component ensures thatstudents have the opportunity to directly compare prediction to observation and motivatesthe development of projects that push the boundaries of the subject. The projects, bytheir nature, readily lend themselves to the formation of inter–disciplinary studentresearch teams. Thus students have the opportunity to learn skills essential for successin today’s workplace including productive team work, critical thinking, problem solving,project management, and effective communication.

Expectations about future motions can influence both perceptual judgements and pursuit eye movements. However, it is not known whether these two effects are due to shared processing, or to separate mechanisms with similar properties. We have addressed this question by providing subjects with prior information about the likely direction of motion in an upcoming random-dot motion display and measuring both the perceptual judgements and pursuit eye movements elicited by the stimulus. We quantified the subjects' responses by computing oculometric curves from their pursuit eye movements and psychometric curves from their perceptual decisions. Our results show that directional cues caused similar shifts in both the oculometric and psychometric curves toward the expected motion direction, with little change in the shapes of the curves. Prior information therefore biased the outcome of both eye movement and perceptual decisions without systematically changing their thresholds. We also found that eye movement and perceptual decisions tended to be the same on a trial-by-trial basis, at a higher frequency than would be expected by chance. Furthermore, the effects of prior information were evident during pursuit initiation, as well as during pursuit maintenance, indicating that prior information likely influenced the early processing of visual motion. We conclude that, in our experiments, expectations caused similar effects on both pursuit and perception by altering the activity of visual motion detectors that are read out by both the oculomotor and perceptual systems. Applying cognitive factors such as expectations at relatively early stages of visual processing could act to coordinate the metrics of eye movements with perceptual judgements.