No description available.

The objective of the Small Robot Technology (SMART) initiative at the Naval Post Graduate School (NPS) is to develop robots for military uses. One of the goals of this program is to create a surf--zone reconnaissance robot to do beachhead surveillance and mine detection. To this end, a prototype robot was created to test the locomotion and navigation functions which will be used on the surf--zone robot. This work consisted of redesigning the steering mechanism, strengthen the structure, improving the electrical distribution and upgrading the communications hardware. Several tests were conducted on both grass and soft sand to evaluate the performance of the locomotion system and the navigation software. The results demonstrated that the robot functions best in soft sand as expected. However, several serious mechanical design flaws were noticed in the body construction and mechanical systems. These flaws, while not detrimental, did negatively impact the performance of the system. Finally, some suggestions for improving future prototypes are discussed. / US Navy (USN) author.

No description available.

No description available.

Most of recent studies indicate that people are negatively predisposed toward utilizing autonomous systems. These findings highlight the necessity of conducting research to better understand the evolution of trust between humans and growing autonomous technologies such as self-driving cars (SDC). This research therefore presents a new approach for real-time trust measurement between passengers and SDCs. We utilized a new structured data collection approach along with a virtual reality (VR) SDC simulator to understand how various autonomous driving scenarios can increase or decrease human trust and how trust can be re-built in the case of incidental failures. To verify our methodology, we designed and conducted an empirical experiment on 50 human subjects. The results of this experiment indicated that most subjects could rebuild trust during a reasonable timeframe after the system demonstrated faulty behavior. Furthermore, we discovered that the cultural background and past trust-related experiences of the subjects affect how they lose or regain their trust in SDCs. Our analysis showed that this model is highly effective for collecting real-time data from human subjects and lays the foundation for more-involved future research in the domain of human trust and autonomous driving. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

abstract: The prospects of commercially available autonomous vehicles are surely tantalizing, however the implementation of these vehicles and their strain on the social dynamics between motorists and pedestrians remains unknown. Questions concerning how autonomous vehicles will communicate safety and intent to pedestrians remain largely unanswered. This study examines the efficacy of various proposed technologies for bridging the communication gap between self-driving cars and pedestrians. Displays utilizing words like “safe” and “danger” seem to be effective in communicating with pedestrians and other road users. Future research should attempt to study different external notification interfaces in real-life settings to more accurately gauge pedestrian responses. / Dissertation/Thesis / Masters Thesis Engineering 2019

<p>This thesis investigates the use of Genetic Programming (GP) to evolve controllers for an autonomous robot.</p><p>GP is a type of Genetic Algorithm (GA) using the Darwinian idea of natural selection and genetic recombination, where the individuals most often is represented as a tree-structure. The GP is used to evolve a population of possible solutions over many generations to solve problems.</p><p>The most common approach used today, to develop controllers for autonomous robots, is to employ a GA to evolve an Artificial Neural Network (ANN). This approach is most often used in simulation only or in conjunction with online evolution; where simulation still covers the largest part of the process.</p><p>The GP has been largely neglected in Behaviour Based Robotics (BBR). The is primarily due to the problem of speed, which is the biggest curse of any standard GP. The main contribution of this thesis is the approach of using a linear representation of the GP in online evolution, and to establish whether or not the GP is feasible in this situation. Since this is not a comparison with other methods, only a demonstration of the possibilities with GP, there is no need for testing the particular test cases with other methods.</p><p>The work in this thesis builds upon the work by Wolfgang Banzhaf and Peter Nordin, and therefore a comparison with their work will be done.</p>

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 111-114).

Wild-type viruses with intrinsic oncolytic capacity in human includes DNA viruses like some autonomous parvoviruses and many RNA viruses. Recent advances in molecular biology have allowed the design of several genetically modified viruses, such as adenovirus and herpes simplex virus that specifically replicate in, and kill tumor cells. However, still several hurdles regarding clinical limitations and safety issues should be overcome before this mode of therapy can become of clinical relevance. It includes limited virus spread in tumor masses, stability of virus in the blood, trapping within the liver sinusoids, transendothelial transfer, and/or vector diffusion of viral particles to tumor cells, limited tumor transduction, immune-mediated inactivation or destruction of the virus. For replication-competent vectors without approved antiviral agents, suicide genes might be used as fail-safe mechanism. Cancer stem cells are a minor population of tumor cells that possess the stem cell property of self-renewal. Therefore, viruses that target the defective self-renewal pathways in cancer cells might lead to improved outcomes. In this thesis, data we generated in the field of oncolytic autonomous parvoviruses are presented. We replaced capsid genes by reporter genes and assessed expression in different types of human cancer cells and their normal counterparts, either at the level of whole cell population, (CAT ELISA) or at the single cell level, (FACS analysis of Green Fluorescent Protein). Cat expression was substantial (up to 10000 times background) in all infected tumor cells, despite variations according to the cell types. In contrast, no gene expression was detected in similarly infected normal cells, (with the exception of an expression slightly above background in fibroblasts.). FACS analysis of GFP expression revealed that most tumor cells expressed high level of GFP while no GFP positive normal cells could be detected with the exception of very few (less than 0.1%) human fibroblast cells expressing high level of GFP. We also replace capsid genes by genes coding for the costimulatory molecules B7-1 and B7-2 and show that, upon infection with B7 recombinant virions, only tumor cells display the costimulatory molecules and their immunogenicity was increased without any effect on normal cells. Using a recombinant MVM containig the Herpes Simplex thymidine kinase gene, we could get efficient killing of most tumor cell types in the presence of ganciclovir, whithout affecting normal proliferating cells. We also produced tetracycline inducible packaging cell lines in order to improve recombinant vectors yields. The prospects and limitations of these different strategies will be discussed. An overview is given of the general mechanisms and genetic modifications by which oncolytic viruses achieve tumor cell-specific replication and antitumor efficacy. However, as their therapeutic efficacy in clinical trials is still not optimal, strategies are evaluated that could further enhance the oncolytic potential of conditionally replicating viruses in conjunction with other standard therapies. Another exciting new area of research has been the harnessing of naturally tumor-homing cells as carrier cells to deliver oncolytic viruses to tumors. The trafficking of these tumor-homing cells (stem cells, immune cells and cancer cells), which support proliferation of the viruses, is mediated by specific chemokines and cell adhesion molecules and we are just beginning to understand the roles of these molecules. Finally, we will explore some ways deserving further study in order to be able to utilize various oncolytic viruses for effective cancer treatment.

This thesis investigates the use of Genetic Programming (GP) to evolve controllers for an autonomous robot. GP is a type of Genetic Algorithm (GA) using the Darwinian idea of natural selection and genetic recombination, where the individuals most often is represented as a tree-structure. The GP is used to evolve a population of possible solutions over many generations to solve problems. The most common approach used today, to develop controllers for autonomous robots, is to employ a GA to evolve an Artificial Neural Network (ANN). This approach is most often used in simulation only or in conjunction with online evolution; where simulation still covers the largest part of the process. The GP has been largely neglected in Behaviour Based Robotics (BBR). The is primarily due to the problem of speed, which is the biggest curse of any standard GP. The main contribution of this thesis is the approach of using a linear representation of the GP in online evolution, and to establish whether or not the GP is feasible in this situation. Since this is not a comparison with other methods, only a demonstration of the possibilities with GP, there is no need for testing the particular test cases with other methods. The work in this thesis builds upon the work by Wolfgang Banzhaf and Peter Nordin, and therefore a comparison with their work will be done.