A testbed for multi-robot systems

This thesis investigates the problem of multiple robot path planning. In the first chapter of the thesis, we propose a general purpose multi-robots testbed Cy-Eye. Typical applications include target detection, tracking, and surveillance can be tested on this testbed. Its architecture makes it suitable for centralized and distributed experiments. In the second chapter, we present one formation control problem. When multiple robots working together, it is often that they have to assign targets among themselves, and then plan and schedule their collision-free paths to their targets. Specifically, we present a navigation strategy for multiple ground-based robots in row crop field. We show that obtaining the solution to the problem of minimizing the length of the distance traveled by the robots, and subsequent rearrangement can lead to paths on which the robots only collide at a few intersections. Controlling the passage of robots at those intersections with local interactions can lead to collision-free paths. In the third chapter, we present the current progress of a multiple player pursuit-evasion game. The objects for the aerial pursuers are maximizing the tracking time for keep multiple evaders in the field of view. We propose a tracking strategy and show the simulation

Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications

Reliable seed yield estimation is an indispensable step in plant breeding programs geared towards cultivar development in major row crops. The objective of this study is to develop a machine learning (ML) approach adept at soybean [Glycine max L. (Merr.)] pod counting to enable genotype seed yield rank prediction from in-field video data collected by a ground robot. To meet this goal, we developed a multi-view image-based yield estimation framework utilizing deep learning architectures. Plant images captured from different angles were fused to estimate the yield and subsequently to rank soybean genotypes for application in breeding decisions. We used data from controlled imaging environment in field, as well as from plant breeding test plots in field to demonstrate the efficacy of our framework via comparing performance with manual pod counting and yield estimation. Our results demonstrate the promise of ML models in making breeding decisions with significant reduction of time and human effort, and opening new breeding methods avenues to develop cultivars

Human Metapneumovirus Inhibits IFN-β Signaling by Downregulating Jak1 and Tyk2 Cellular Levels

Human metapneumovirus (hMPV), a leading cause of respiratory tract infections in infants, inhibits type I interferon (IFN) signaling by an unidentified mechanism. In this study, we showed that infection of airway epithelial cells with hMPV decreased cellular level of Janus tyrosine kinase (Jak1) and tyrosine kinase 2 (Tyk2), due to enhanced proteosomal degradation and reduced gene transcription. In addition, hMPV infection also reduced the surface expression of type I IFN receptor (IFNAR). These inhibitory mechanisms are different from the ones employed by respiratory syncytial virus (RSV), which does not affect Jak1, Tyk2 or IFNAR expression, but degrades downstream signal transducer and activator of transcription proteins 2 (STAT2), although both viruses are pneumoviruses belonging to the Paramyxoviridae family. Our study identifies a novel mechanism by which hMPV inhibits STAT1 and 2 activation, ultimately leading to viral evasion of host IFN responses

A testbed for multi-robot systems

This thesis investigates the problem of multiple robot path planning. In the first chapter of the thesis, we propose a general purpose multi-robots testbed Cy-Eye. Typical applications include target detection, tracking, and surveillance can be tested on this testbed. Its architecture makes it suitable for centralized and distributed experiments. In the second chapter, we present one formation control problem. When multiple robots working together, it is often that they have to assign targets among themselves, and then plan and schedule their collision-free paths to their targets. Specifically, we present a navigation strategy for multiple ground-based robots in row crop field. We show that obtaining the solution to the problem of minimizing the length of the distance traveled by the robots, and subsequent rearrangement can lead to paths on which the robots only collide at a few intersections. Controlling the passage of robots at those intersections with local interactions can lead to collision-free paths. In the third chapter, we present the current progress of a multiple player pursuit-evasion game. The objects for the aerial pursuers are maximizing the tracking time for keep multiple evaders in the field of view. We propose a tracking strategy and show the simulation.</p

Evaluation of public transportation station area accessibility based on walking perception

Public transportation (PT) often fails to provide door-to-door service. Passengers often have to walk a distance to reach their destination after getting off the public transportation station. Therefore, the walking accessibility of the station area directly affects the attractiveness of the PT. For walking, accurate calculation or prediction of accessibility should consider not only the objective distance, but also the environment and psychological perception factors of pedestrians. This paper aims to map the pedestrian perceived cost to the transportation environment to evaluate the walking accessibility of the public transportation station area accurately. From the perspective of psychological perception of walking environment, four key impedance factors are selected and a pedestrian perceived impedance model is established. Then an evaluation model of station area accessibility is set employing POIs (Point of Interests) based on the accumulative opportunity method. Finally, the case is given to show the application of the model. The results show that the number of crosswalks with signal lights, mixed use of sidewalk and non-motorized lane, the obstacle quantity and the vehicle entrance quantity on sidewalks can increase perceived impedance significantly. For example, pedestrians are willing to spend 4.21 extra minutes to adopt routes with one fewer obstacle per 100 meters. Within 10 minutes of walking time, walking perception has a greater impact on station area accessibility. The perceived walking time thresholds for evaluating bus and rail transit station area accessibility are recommended to be 15 minutes and 20 minutes, respectively. The evaluation results can provide a reliable basis for improving the walking network around public transportation station