@article{nguyen_ore_castro-bolinaga_hall_young_2024, title={TOWARDS AUTONOMOUS, OPTIMAL WATER SAMPLING WITH AERIAL AND SURFACE VEHICLES FOR RAPID WATER QUALITY ASSESSMENT}, volume={67}, ISSN={["2769-3287"]}, DOI={10.13031/ja.15796}, abstractNote={Highlights A practical workflow for optimizing sampling tours for a team of surface and aerial vehicles was developed. Proposed workflow considers unique sensing capabilities of surface vehicles when assigning sampling locations. Likely optimal tours can be found in less than 30 s for practical water quality sampling requirements. Abstract. Most current marine aquaculture operations are located in coastal estuarine areas within one mile of the shoreline, and water quality in these production areas can quickly become unfavorable due to hydrodynamic processes and excessive runoff. The deployment of autonomous, robotic systems can improve the speed and spatiotemporal resolution of water sampling and sensing in mariculture production areas to assess water quality in the context of food safety. Specifically, teams of both aerial and surface vehicles can be deployed simultaneously to capitalize on the benefits of each system; however, a method to optimally design a feasible sampling tour for each robot is needed to maximize sample capacity and ensure efficient water sampling missions. This research brief presents the problem formulation and a solution method to determine optimal tours for a team of aquatic surface and aerial vehicles while considering different vehicle sampling capacities and endurance constraints. This method was implemented to design sampling missions of 15, 20, and 30 samples in both a 0.25 km2 and 3.9 km2 site, using sampling capacity and endurance constraints corresponding to real-world robots used for water sampling in mariculture environments. Results indicate that this optimization problem can be solved in near-real time in the field and yields feasible sampling tours for surface and aerial vehicles under different constraints. This work is a practical step towards developing teams of collaborative robots to persistently monitor adverse mariculture growing conditions so producers can implement data-driven, timely management strategies. Keywords: Mariculture, Robotics, Traveling salesperson problem, Vehicle routing.}, number={1}, journal={JOURNAL OF THE ASABE}, author={Nguyen, Anh and Ore, John -Paul and Castro-Bolinaga, Celso and Hall, Steven G. and Young, Sierra}, year={2024}, pages={91–98} }
 @article{moussa_ore_2022, title={Maktub: Lightweight Robot System Test Creation and Automation}, ISSN={["1527-1366"]}, DOI={10.1145/3551349.3559531}, abstractNote={The rapid expansion of robotics relies on properly configuring and testing hardware and software. Due to the expense and hazard of real-world testing on hardware, robot system testing increasingly utilizes extensive simulation. Creating robot simulation tests requires specialized skills in robot programming and simulation tools. While there are many platforms and tool-kits to create these simulations, they can be cumbersome when combined with automated testing. We present Maktub: a tool for creating tests using Unity and ROS. Maktub leverages the extensive 3D manipulation capabilities of Unity to lower the barrier in creating system tests for robots. A key idea of Maktub is to make tests without needing robotic software development skills. A video demonstration of Maktub can be found here: https://youtu.be/c0Bacy3DlEE, and the source code can be found at https://github.com/RobotCodeLab/Maktub.}, journal={PROCEEDINGS OF THE 37TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING, ASE 2022}, author={Moussa, Amr and Ore, John-Paul}, year={2022} }
 @article{ore_detweiler_elbaum_2021, title={An Empirical Study on Type Annotations: Accuracy, Speed, and Suggestion Effectiveness}, volume={30}, ISSN={["1557-7392"]}, DOI={10.1145/3439775}, abstractNote={Type annotations connect variables to domain-specific types. They enable the power of type checking and can detect faults early. In practice, type annotations have a reputation of being burdensome to developers. We lack, however, an empirical understanding of how and why they are burdensome. Hence, we seek to measure the baseline accuracy and speed for developers making type annotations to previously unseen code. We also study the impact of one or more type suggestions. We conduct an empirical study of 97 developers using 20 randomly selected code artifacts from the robotics domain containing physical unit types. We find that subjects select the correct physical type with just 51% accuracy, and a single correct annotation takes about 2 minutes on average. Showing subjects a single suggestion has a strong and significant impact on accuracy both when correct and incorrect, while showing three suggestions retains the significant benefits without the negative effects. We also find that suggestions do not come with a time penalty. We require subjects to explain their annotation choices, and we qualitatively analyze their explanations. We find that identifier names and reasoning about code operations are the primary clues for selecting a type. We also examine two state-of-the-art automated type annotation systems and find opportunities for their improvement.}, number={2}, journal={ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY}, author={Ore, John-Paul and Detweiler, Carrick and Elbaum, Sebastian}, year={2021}, month={Mar} }
 @article{asadi_haritsa_han_ore_2021, title={Automated Object Manipulation Using Vision-Based Mobile Robotic System for Construction Applications}, volume={35}, ISSN={["1943-5487"]}, url={http://dx.doi.org/10.1061/(asce)cp.1943-5487.0000946}, DOI={10.1061/(ASCE)CP.1943-5487.0000946}, abstractNote={AbstractIn the last decade, automated object manipulation for construction applications has received much attention. However, the majority of existing systems are situated in a fixed location. They...}, number={1}, journal={JOURNAL OF COMPUTING IN CIVIL ENGINEERING}, publisher={American Society of Civil Engineers (ASCE)}, author={Asadi, Khashayar and Haritsa, Varun R. and Han, Kevin and Ore, John-Paul}, year={2021}, month={Jan} }