• Archives of design research
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• v.18 no.2 s.60
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• pp.155-164
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• 2005

Home-service robots need to have sufficient spatial information about the surroundings for interacting with human intelligently and performing services efficiently. It is very important to investigate the efficient interaction style that supports map building task through human-robot collaboration. We first analyzed map building task with a cleaning robot and drew 4 design factors and tentative solutions, including map building procedure (task-preferred procedure/space- preferred procedure), LCD display installation (robot/robot+remote control), navigation method (push type/pull type), feedback modality(GUI/GUI+TTS). The design factors and tentative solutions were defined as independent variables and levels. This research investigated how those variables affect to the human task performance and behavior in map building tast. 8 kinds of experiment prototypes were built and usability test among 16 house wives was conducted for acquiring empirical data. As the experiment result, in terms of map building procedure, space-preferred procedure indicated better task performance than task-proffered procedure as we expected. For the LCD display installation factor, remote control with LCD display indicated higher task performance and subjective satisfaction. In robot navigation method, it was very difficult to find a significant difference between push type and pull type which contrary to our expectation. In fact, push type indicated higher subjective satisfaction. Also in feedback modality, we have acquired negative feedback an additional TTS operation guidance. It seems that robot's autonomy before achieving spatial information is rudiment condition which means users are just interacting with a mobile appliance. Thus they prefer remote-control-based interaction style in robot map building process as they used in traditional appliance control.

• Convergence Security Journal
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• v.19 no.1
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• pp.145-152
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• 2019

In the era of the 3rd Offset Strategy led by the 4th Industrial Revolution, the use of robots with AI and autonomous abilities is becoming more active in military field. The 3rd Offset Strategy is based on the technology of the 4th Industrial Revolution, and S. Korea is heavily dependent on US military technology and is directly and indirectly influenced by the military revolutionary strategy and the alliance relationship. There are many issues that need to be addressed beyond technical maturity for both strategies to be successfully applied in the military. However, there are few discussions about these limitations in many studies and media reports in comparison with the advantages of the techniques. This research describes robot ethics & technology unbalance, problems of autonomous functions, display fatigue induced by VR/AR/MR, cyber/network security to be solved for successful strategies, also the solutions are addressed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.140-146
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• 2013

In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.41-49
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• 2022

With the advancement of intelligent vehicles and unmanned systems, there is a growing interest in underwater surveys using autonomous marine vehicles (AMVs). This study presents an automated planning strategy for a long-term survey mission using a fleet of AMVs consisting of autonomous surface vehicles and autonomous underwater vehicles. Due to the complex nature of the mission, the actions of the vehicle must be of high-level abstraction, which means that the actions indicate not only motion of the vehicle but also symbols and semantics, such as those corresponding to deploy, charge, and survey. For automated planning, the planning domain definition language (PDDL) was employed to construct a mission planner for realizing a powerful and flexible planning system. Despite being able to handle abstract actions, such high-level planners have difficulty in efficiently optimizing numerical objectives such as obtaining the shortest route given multiple destinations. To alleviate this issue, a widely known technique in operations research was additionally employed, which limited the solution space so that the high-level planner could devise efficient plans. For a comprehensive evaluation of the proposed method, various PDDL-based planners with different parameter settings were implemented, and their performances were compared through simulation. The simulation result shows that the proposed method outperformed the baseline solutions by yielding plans that completed the missions more quickly, thereby demonstrating the efficacy of the proposed methodology.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.160-167
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• 2023

This study focuses on the development of a Last-Mile delivery service using unmanned vehicles to deliver goods directly to the end consumer utilizing drones to perform autonomous delivery missions and an image-based precision landing algorithm for handoff to a robot in an intermediate facility. As the logistics market continues to grow rapidly, parcel volumes increase exponentially each year. However, due to low delivery fees, the workload of delivery personnel is increasing, resulting in a decrease in the quality of delivery services. To address this issue, the research team conducted a study on a Last-Mile delivery service using unmanned vehicles and conducted research on the necessary technologies for drone-based goods transportation in this paper. The flight scenario begins with the drone carrying the goods from a pickup location to the rooftop of a building where the final delivery destination is located. There is a handoff facility on the rooftop of the building, and a marker on the roof must be accurately landed upon. The mission is complete once the goods are delivered and the drone returns to its original location. The research team developed a mission planning algorithm to perform the above scenario automatically and constructed an algorithm to recognize the marker through a camera sensor and achieve a precision landing. The performance of the developed system has been verified through multiple trial operations within ETRI.