A Localized Autonomous Control Algorithm For Robots With Heterogeneous Capabilities In A Multi-Tier Architecture

This dissertation makes two contributions to the use of the Blackboard Architecture for command. The use of boundary nodes for data abstraction is introduced and the use of a solver-based blackboard system with pruning is proposed. It also makes contributions advancing the engineering design process in the area of command system selection for heterogeneous robotic systems. It presents and analyzes data informing decision making between centralized and distributed command systems and also characterizes the efficacy of pruning across different experimental scenarios, demonstrating when it is effective or not. Finally, it demonstrates the operations of the system, raising the technology readiness level (TRL) of the technology towards a level suitable for actual mission use. The context for this work is a multi-tier mission architecture, based on prior work by Fink on a “tier scalable” architecture. This work took a top-down approach where the superior tiers (in terms of scope of visibility) send specific commands to craft in lower tiers. While benefitting from the use of a large centralized processing center, this approach is limited in responding to failures and interference. The work presented herein has involved developing and comparatively characterizing centralized and decentralized (where superior nodes provide information and goals to the lower-level craft, but decisions are made locally) Blackboard Architecture based command systems. Blackboard Architecture advancements (a solver, pruning, boundary nodes) have been made and tested under multiple experimental conditions

Lemons to Lemonade: Refining an Active Learning Course for Delivery During a Pandemic

The Spring semester of 2020 was a time of unanticipated and unprecedented rapid change for higher education in the United States. The COVID-19 pandemic struck the United States midway through the semester forcing colleges and universities to rapidly take courses online with minimal time to prepare. North Dakota was, comparatively, fortunate in that the transition occurred over spring break; however, initially the online period was only supposed to last for two weeks. This poster presents the process that was used to rapidly change an active learning course, which was designed for in person delivery, over to being held entirely online.https://openprairie.sdstate.edu/asee_nmws_2020_posters/1006/thumbnail.jp

Report on the First NSF CubeSat Software Research Experience for Undergraduates

For three summers, 2015, 2016 and 2017, undergraduate students from around the United States came to North Dakota to participate in a NSF sponsored Research Experience for Undergraduates program focused on CubeSat software. This program was the first NSF-sponsored Research Experience for Undergraduates program focused on CubeSat software. This paper presents the final results from all three years of that program

A Blackboard-style decision-making system for multi-tier craft control and its evaluation

This article presents an approach for decision-making in support of the control of an autonomous system of multiple tiers of robots (e.g., satellite, aerial and ground) based on the Blackboard architectural style. Under the proposed approach, the system evaluates prospective approaches for goal satisfaction (identified by user selected final rules), identifies the lowest-cost solution and determines the best path to achieving the goal, via the analysis of the Blackboard rule and action set. Two different approaches to this rule and action path generation are discussed. This article presents the proposed Blackboard-style architecture for autonomous multi-tier control and describes its implementation. The benefits and drawbacks of the Blackboard-style approach are analysed, its extrapolation to the control of multiple heterogeneous craft is presented and the tradeoffs between the two approaches to rule-path generation are assessed

Statistical Analysis of CubeSat Mission Failure

There are multiple common reasons for CubeSats’ failure. These include power, mechanical, and communications issues. Some have suggested that the problem lies within the design and development process itself, in that universities and research institutions mainly focus on system and component level designs, while neglecting requirements’ elicitation needed beforehand. A survey was conducted during the 14th Annual CubeSat Workshop at CalPoly, San Luis Obispo, to identify the challenges and needs of such groups and initial results from this survey and its analysis are reported in this paper. This survey was conducted with students in the U. S. and Europe, working on small spacecraft development and majoring in disciplines including computer science and mechanical engineering. The survey considered multiple factors prospectively associated with mission success or failure, including the possibility of adding or deleting components into/from the system design and system modifications’ feasibility. Additionally, the respondents were asked the objectives of their CubeSat mission and whether their system design covered the entire system (e.g., structure, behavior, requirements, and system parametric). The problems identified by them related to tools, models, or both have also been reported. Finally, participants were asked whether they helped in reducing the system testing time or employed a CubeSat reference model. This paper concludes with a discussion regarding what has been learned from data analysis. Plans for future work are also discussed

The Use of the Blackboard Archiecture for a Decision making System for the Control of Craft with various Actuator and Movement Capabilities

This paper provides an overview of an approach to the control of multiple craft with heterogeneous movement and actuation characteristics that is based on the Blackboard software architecture. An overview of the Blackboard architecture is provided. Then, the operational and mission requirements that dictate the need for autonomous control are characterized and the utility of the Blackboard architecture is for meeting these requirements is discussed. The performance of a best-path solver and naïve solver are compared. The results demonstrate that the best-path solver outperforms the naïve solver in the amount of time taken to generate a solution, however, the number of solver-runs to be executed against the Blackboard must be sufficient to allow the lower individual-run times to offset the time required to propagate the data utilized by the best-path solver for solution generation through the database. The existence of other justifications for this approach (even if the number of runs for each data propagation cycle is not sufficient) is also discussed

Development and Assessment of Courses in Defensive Security and Ethical Hacking

In order to combat malicious actors of the digital age, cybersecurity experts have quickly become essential in almost every company. New employees must be ready to \u27hit the ground running\u27 in this dynamic and frequently changing fields. To effectively prepare students for careers in cybersecurity , enhancements are needed to traditional class-based lecture techniques. This work presents and evaluates two different methodologies used in cybersecurity education: a gamification approach which used a capture the flag model and competition -based approach.https://openprairie.sdstate.edu/asee_nmws_2020_posters/1000/thumbnail.jp

Integrating Hybrid-Flexible Course Delivery with General Education Computer Science Courses

The Hybrid-Flexible (HyFlex) course delivery format was developed at San Francisco State University to make SDSU’s instructional technologies master’s degree program accessible to working adults. Under the HyFlex model, instructors build content for both a fully online course and for a traditional ‘face-to-face’ classroom environment. Both have the same learning outcomes for each week, so that students can move between online and in-person participation in the course seamlessly. This poster covers the adaptation of CSCI 159, Computer Science Problem Solving, to the HyFlex model. The implementation of this course differs from the model in that it was entirely online but implemented HyFlex principles.https://openprairie.sdstate.edu/asee_nmws_2020_posters/1001/thumbnail.jp

Development of an Autonomous Reverse Engineering Capability for Controller Area Network Messages to Support Autonomous Control Retrofits

As the autonomous vehicle industry continues to grow, various companies are exploring the use of aftermarket kits to retrofit existing vehicles with semi-autonomous capabilities. However, differences in implementation of the controller area network (CAN) used by each vehicle manufacturer poses a significant challenge to achieving large-scale implementation of retrofits. To address this challenge, this research proposes a method for reverse engineering the CAN channels associated with a vehicle's accelerator and brake pedals, without any prior knowledge of the vehicle. By simultaneously recording inertial measurement unit (IMU) and CAN data during vehicle operation, the proposed algorithms can identify the CAN channels that correspond to each control. During testing of six vehicles from three manufacturers, the proposed method was shown to successfully identify the CAN channels for the accelerator pedal and brake pedal for each vehicle tested. These promising results demonstrate the potential for using this approach for developing aftermarket autonomous vehicle kits - potentially with additional research to facilitate real-time use. Notably, the proposed system has the potential to maintain its effectiveness despite changes in vehicle CAN standards, and it could potentially be adapted to function with any vehicle communications medium