Bed Bug Movement response to Co2 With Implications for Unmanned Ariel Vehciles Systems
Faculty Mentor Name
Corraine McNeill, Bryan Watson, Karen Mittelstadt
Format Preference
Poster
Abstract
In the last decade, there has been increasing research interest in the coordinated use of multi-unmanned aerial vehicles (UAVs), as modern aerospace systems recognize the advantage of networking many small and simple agents working together. Biologically inspired design has been used in the past to successfully create a variety of swarm algorithms. Previous biological research has focused on the behaviors of ants and bees. Bed bugs were proposed as a novel source of inspiration because their behaviors exhibit many of the desired characteristics of UAV swarm performance. The common bed bug, Cimex lectularius L., (Hemiptera: Cimicidae), is an ectoparasite that lives among vertebrate hosts, most commonly humans. Bed bugs aggregate based on several host attractants, with CO2 being the most attractive host cue that elicits the most movement. Bed bugs demonstrate sophisticated group decision-making while considering these criteria. Their responses to these factors can be quantified by recording their movement patterns based on a CO2 stimulus. Various CO2 concentrations were allowed into an enclosed testing arena through ports at the end of the apparatus. Responses to CO2 were recorded for individual and grouped bed bugs, based on gender and hunger status at every 305 mm within the testing arena. It was hypothesized that the collective decision-making movement process of bed bugs can be observed because their olfactory system will detect CO2 and aggregation pheromones. Preliminary results show that bed bugs that are 610 mm from the CO2 source will travel shorter distances, much faster, and with more angular movement, compared to bed bugs with no CO2 source. This research will not only help improve on bed bug behavior and pest management practices, but UAV swarm system designs will benefit from algorithms that are created from these bed bug movement patterns that will allow for better coordinated movements and decision-making.
Bed Bug Movement response to Co2 With Implications for Unmanned Ariel Vehciles Systems
In the last decade, there has been increasing research interest in the coordinated use of multi-unmanned aerial vehicles (UAVs), as modern aerospace systems recognize the advantage of networking many small and simple agents working together. Biologically inspired design has been used in the past to successfully create a variety of swarm algorithms. Previous biological research has focused on the behaviors of ants and bees. Bed bugs were proposed as a novel source of inspiration because their behaviors exhibit many of the desired characteristics of UAV swarm performance. The common bed bug, Cimex lectularius L., (Hemiptera: Cimicidae), is an ectoparasite that lives among vertebrate hosts, most commonly humans. Bed bugs aggregate based on several host attractants, with CO2 being the most attractive host cue that elicits the most movement. Bed bugs demonstrate sophisticated group decision-making while considering these criteria. Their responses to these factors can be quantified by recording their movement patterns based on a CO2 stimulus. Various CO2 concentrations were allowed into an enclosed testing arena through ports at the end of the apparatus. Responses to CO2 were recorded for individual and grouped bed bugs, based on gender and hunger status at every 305 mm within the testing arena. It was hypothesized that the collective decision-making movement process of bed bugs can be observed because their olfactory system will detect CO2 and aggregation pheromones. Preliminary results show that bed bugs that are 610 mm from the CO2 source will travel shorter distances, much faster, and with more angular movement, compared to bed bugs with no CO2 source. This research will not only help improve on bed bug behavior and pest management practices, but UAV swarm system designs will benefit from algorithms that are created from these bed bug movement patterns that will allow for better coordinated movements and decision-making.