• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.8
• /
• pp.953-964
• /
• 2010

In this study, we proposed duty executions to confine a robot in a specific place with multiple robots. The proposed method involved the use of a role classifier for assigning labor roles, behavior selector for each robot, and a collaboration manager for handling complex situations. Further, we verified the validity of the proposed method by performing simulations to confine a robot in the specific location by using multiple robots.

• Proceedings of the KIEE Conference
• /
• 2001.11c
• /
• pp.428-430
• /
• 2001

다수의 자율이동로봇으로 구성되는 다개체 시스템에서의 협조행동을 위해서 각 개체는 주변환경의 인식뿐만 아니라 환경변화에 적응할 수 있는 추론능력이 요구된다. 이에 본 논문에서는 강화학습을 이용하여 동적으로 변화하는 환경 하에서 개체들이 스스로 학습하고 대처할 수 있는 협조행동 방법을 제시한다. 제안한 방법을 먹이와 포식자 문제에 적용하여 포식자 로봇간의 협조행동을 구현하였다. 여러 대로 구성된 포식자 로봇은 회피가 목적인 먹이로봇을 추적하여 포획하는 것이 임무이며 포식자 로봇들 간의 협조행동을 위해 각 상태에 따른 최적의 행동방식을 찾는데 강화학습을 이용한다.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2011.06a
• /
• pp.291-292
• /
• 2011

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.8
• /
• pp.696-702
• /
• 2004

An optimal trajectory generation algorithm for capturing a moving object by a mobile robot in real-time is proposed in this paper. The linear and rotational velocities of the moving object are estimated using the Kalman filter, as a state estimator. For the estimation, the moving object is tracked by a 2-DOF active camera mounted on the mobile robot, which enables a mobile manipulator to track the mobile robot until the capturing moment. The optimal trajectory for capturing the moving object is dependent on the initial conditions of the mobile robot as well as the moving object. Therefore, real-time trajectory planning for the mobile robot is definitely required for the successful capturing of the moving object. The performance of proposed algorithm is verified through the real experiments and the superiority is demonstrated by comparing to other algorithms.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.9
• /
• pp.741-748
• /
• 2001

In this paper, we propose a method of tracking and capturing a moving object by a mobile robot. The position of the moving object is acquired from the relation through color-based image information from a 2-DOF active camera mounted on the mobile robot. The direction and rotational angular velocity of the moving object are estimated using a state estimator. A Kalman fiber is used as the state estimator for taking characteristics of robustness against noises and uncertainties included in the input data. After estimating the trajectory of the moving object, we decide on the optimal trajectory and plan the motion of the mobile robot to capture the target object within the shortest distance and time. The effectiveness of the proposed method is demonstrated by the simulations and experiments.

• Journal of Ocean Engineering and Technology
• /
• v.30 no.2
• /
• pp.141-149
• /
• 2016

In this technical note, the issues and challenges for the launch and recovery systems (LARS) and related techniques for the operation of an underwater robot from a manned platform are considered. Various types of LARS fitted to specific manned platforms, surface or sub-surface, are surveyed and categorized. The current UUV launch and recovery systems from surface ships and submarines utilize time consuming processes. As underwater robot technologies evolve and their roles are defined, safe and effective launch and recovery methods should be developed capable of reliable and efficient operations, particularly at a high sea state. To improve the existing underwater robot capabilities, LARS technology maturation is required in the near term, leading to the ability to incorporate autonomous LARS for an underwater robot on a manned platform. In the near term, particular emphasis should be placed on UUV LARS, which are surface ship based, with submarine based systems in the long term. Furthermore, for a dedicated LARS ship, independent of the existing host ship type, particular emphasis should be given to fully utilizing the capabilities of underwater robots.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.2
• /
• pp.145-153
• /
• 2006

An optimal capturing trajectory for a moving object is proposed in this paper based on the observation that a single-curvature path is more accurate than double-or triple-curvature paths. Moving distance, moving time, and trajectory error are major factors considered in deciding an optimal path for capturing the moving object. That is, the moving time and distance are minimized while the trajectory error is maintained as small as possible. The three major factors are compared for the single and the double curvature trajectories to show superiority of the single curvature trajectory. Based upon the single curvature trajectory, a kinematics model of a mobile robot is proposed to follow and capture the moving object, in this paper. A capturing scenario can be summarized as follows: 1. Motion of the moving object has been captured by a CCD camera., 2. Position of the moving object has been estimated using the image frames, and 3. The mobile robot tries to follow the moving object along the single curvature trajectory which matches positions and orientations of the moving object and the mobile robot at the final moment. Effectiveness of the single curvature trajectory modeling and capturing algorithm has been proved, through simulations and real experiments using a 2-DOF wheel-based mobile robot.