Seoul National University · Engineering
Professor Dabin Kim's research lab specializes in perception-aware control and planning for autonomous aerial vehicles, with a strong focus on vision-based navigation, safe trajectory generation, and cooperative robotics. The lab develops advanced control frameworks that integrate perception constraints—such as visibility of landmarks or points of interest—into real-time control and optimization, ensuring both task performance and operational safety. Key research directions include reference governor design for nonlinear systems, learning-based Lyapunov functions for stability verification, and novel multirotor architectures like the T³-multirotor for enhanced maneuverability and payload tracking. The lab emphasizes theoretical guarantees combined with practical implementation for real-world UAV applications.
Figures are computed from collected data and may differ slightly.
Visual navigation has been widely used for state estimation of micro aerial vehicles (MAVs). For stable visual navigation, MAVs should generate perception-aware paths which guarantee enough visible landmarks. Many previous works on perception-aware path planning focused on sampling-based planners. However, they may suffer from sample inefficiency, which leads to computational burden for finding a global optimal path. To address this issue, we suggest a perception-aware path planner which utilize
For safe vision-based control applications, perception-related constraints have to be satisfied in addition to other state constraints. In this paper, we deal with the problem where a multirotor equipped with a camera needs to maintain the visibility of a point of interest while tracking a reference given by a high-level planner. We devise a method based on reference governor that, differently from existing solutions, is able to enforce control-level visibility constraints with theoretically ass
Vision sensors are extensively used for localizing a robot's pose, particularly in environments where global localization tools such as GPS or motion capture systems are unavailable. In many visual navigation systems, localization is achieved by detecting and tracking visual features or landmarks, which provide information about the sensor's relative pose. For reliable feature tracking and accurate pose estimation, it is crucial to maintain visibility of a sufficient number of features. This req
This paper suggests a new cooperative transportation system with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$T$</tex> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> -multirotors. From the promising characteristics of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$T$</tex> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http:
For safe vision-based control applications, perception-related constraints have to be satisfied in addition to other state constraints. In this paper, we deal with the problem where a multirotor equipped with a camera needs to maintain the visibility of a point of interest while tracking a reference given by a high-level planner. We devise a method based on reference governor that, differently from existing solutions, is able to enforce control-level visibility constraints with theoretically ass
A case of persistent Ralstonia mannitolilytica bacteremia in the neonatal intensive care unit prompted source investigation due to its rarity.After an extensive investigation, a contaminated ultrasonic nebulizer was identified as the source, and the infection was controlled by removing the source.This study emphasizes the importance of further investigations, even in single cases of rare pathogens.
Constraint admissible positively invariant (CAPI) sets play a pivotal role in ensuring safety in control and planning applications, such as the recursive feasibility guarantee of explicit reference governor and model predictive control. However, existing methods for finding CAPI sets for nonlinear systems are often limited to single equilibria or specific system dynamics. This limitation underscores the necessity for a method to construct a CAPI set for general reference tracking control and a b
Constraint admissible positively invariant (CAPI) sets play a pivotal role in ensuring safety in control and planning applications, such as the recursive feasibility guarantee of explicit reference governor and model predictive control. However, existing methods for finding CAPI sets for nonlinear systems are often limited to single equilibria or specific system dynamics. This limitation underscores the necessity for a method to construct a CAPI set for general reference tracking control and a b
Visual navigation has been widely used for state estimation of micro aerial vehicles (MAVs). For stable visual navigation, MAVs should generate perception-aware paths which guarantee enough visible landmarks. Many previous works on perception-aware path planning focused on sampling-based planners. However, they may suffer from sample inefficiency, which leads to computational burden for finding a global optimal path. To address this issue, we suggest a perception-aware path planner which utilize
There is need for a legal and social system that ensures equal access to e-books for disabled people and non-disabled people. To enable disabled people and older people to use e-books conveniently, the National Library for the Disabled established the e-book accessibility certification system that certifies quality and issues marks for e-books that conform to e-book accessibility standards. The system is classified into the quality certification stage and certification evaluation stage. The q
Vision sensors are extensively used for localizing a robot's pose, particularly in environments where global localization tools such as GPS or motion capture systems are unavailable. In many visual navigation systems, localization is achieved by detecting and tracking visual features or landmarks, which provide information about the sensor's relative pose. For reliable feature tracking and accurate pose estimation, it is crucial to maintain visibility of a sufficient number of features. This req
Achieving full autonomy in robotics requires safe navigation and reliable collision avoidance in unknown environments. This demands robust perception and mapping, as well as control strategies that can effectively utilize environmental information while enforcing safety constraints. However, to address noisy and sparse measurements from inexpensive onboard sensors commonly used on low-power mobile platforms, probabilistic and continuous map representations have emerged as more effective alternat
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