Search for: All records

This paper considers path planning with resource constraints and dynamic obstacles for an unmanned aerial vehicle (UAV), modeled as a Dubins agent. Incorporating these complex constraints at the guidance stage expands the scope of operations of UAVs in challenging environments containing path-dependent integral constraints and time-varying obstacles. Path-dependent integral constraints, also known as resource constraints, can occur when the UAV is subject to a hazardous environment that exposes it to cumulative damage over its traversed path. The noise penalty function was selected as the resource constraint for this study, which was modeled as a path integral that exerts a path-dependent load on the UAV, stipulated to not exceed an upper bound. Weather phenomena such as storms, turbulence and ice are modeled as dynamic obstacles. In this paper, ice data from the Aviation Weather Service is employed to create training data sets for learning the dynamics of ice phenomena. Dynamic mode decomposition (DMD) is used to learn and forecast the evolution of ice conditions at flight level. This approach is presented as a computationally scalable means of propagating obstacle dynamics. The reduced order DMD representation of time-varying ice obstacles is integrated with a recently developed backtracking hybridA∗ graph search algorithm. The backtracking mechanism allows us to determine a feasible path in a computationally scalable manner in the presence of resource constraints. Illustrative numerical results are presented to demonstrate the effectiveness of the proposed path-planning method. 

In the past three years, the COVID-19 pandemic has caused serious health, environmental, societal, and economic challenges globally. Sterilization is one of the most efficient methods to mitigate the spread of infectious viruses like SARS-CoV-2. However, extreme sterilization practices can cause serious health and environmental problems worldwide. Heat, ultraviolet C (UVC), and chemical disinfectants require high energy consumption and can cause health concerns, environmental pollution, and chemical overuse. In this paper, we evaluated the efficiency of corona discharge (CD) as an environmentally and energy-friendly sterilization method on different surfaces for sterilization. It was confirmed that CD is an efficient sterilization process for most surfaces and personal protective equipment (PPE). CD allows for a reduction in disinfectant use, addresses the PPE shortage problem, and reduces plastic pollution and biowaste. The air sterilization effect of CD creates a promising option to reduce airborne pathogens. To address the safety concerns of CD, the heat, UVC, and ozone emissions of CD were confirmed to be within a safe range. A wireless, affordable CD robot was developed with the capability to scan along pre-designed paths while having the capability to avoid static and moving obstacles. Automated CD devices and robots can be favorable sterilization solutions for the future as a contactless, more environmentally friendly, efficient, affordable, and portable solution.