Robotics Commons^™

Certification Basis For A Fully Autonomous Uncrewed Passenger Carrying Urban Air Mobility Aircraft, Steve Price

Student Works

The Urban Air Mobility campaign has set a goal to efficiently transport passengers and cargo in urban areas of operation with autonomous aircraft. This concept of operations will require aircraft to utilize technology that currently does not have clear regulatory requirements. This report contains a comprehensive analysis and creation of a certification basis for a fully autonomous uncrewed passenger carrying rotorcraft for use in Urban Air Mobility certified under Title 14 Code of Federal Regulations Part 27. Part 27 was first analyzed to determine the applicability of current regulations. The fully electric propulsion system and fully autonomous flight control system …

Robotic Olfactory-Based Navigation With Mobile Robots, Lingxiao Wang

Doctoral Dissertations and Master's Theses

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. It has been viewed as challenging due to the turbulent nature of airflows and the resulting odor plume characteristics. The key to correctly finding an odor source is designing an effective olfactory-based navigation algorithm, which guides the robot to detect emitted odor plumes as cues in finding the source. This dissertation proposes three kinds of olfactory-based navigation methods to improve search efficiency while maintaining a low computational cost, incorporating different machine learning and artificial intelligence methods.

A. …

Administrative Law In The Automated State, Cary Coglianese

All Faculty Scholarship

In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …

Design And Implementation Of An Artificial Neural Network Controller For Quadrotor Flight In Confined Environment, Ahmed Mekky

Mechanical & Aerospace Engineering Theses & Dissertations

Quadrotors offer practical solutions for many applications, such as emergency rescue, surveillance, military operations, videography and many more. For this reason, they have recently attracted the attention of research and industry. Even though they have been intensively studied, quadrotors still suffer from some challenges that limit their use, such as trajectory measurement, attitude estimation, obstacle avoidance, safety precautions, and land cybersecurity. One major problem is flying in a confined environment, such as closed buildings and tunnels, where the aerodynamics around the quadrotor are affected by close proximity objects, which result in tracking performance deterioration, and sometimes instability. To address this …

Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr

All Faculty Scholarship

Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while others …

Leveraging Area Bounds Information For Autonomous Multi-Robot Exploration, Tsung-Ming Liu, Damian M. Lyons

Faculty Publications

In this paper we propose an approach, the Space-Based Potential Field (SBPF) approach, to controlling multiple robots for area exploration missions that focus on robot dispersion. The SBPF method is based on a potential field approach that leverages knowledge of the overall bounds of the area to be explored. This additional information allows a simpler potential field control strategy for all robots but which nonetheless has good dispersion and overlap performance in all the multi-robot scenarios while avoiding potential minima. Both simulation and robot experimental results are presented as evidence.