• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.587-590
• /
• 2003

In this paper, the control of the differential drive wheeled mobile robot (DDWMR) is studied. Because the DDWMR have non-holonomic constraints, it cannot be stabilized by smooth feedback. The T-S fuzzy model for the DDWMR is presented and a control algorithm Is developed by well known PID control and LMI based regional pole-placement.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2010.05a
• /
• pp.79-80
• /
• 2010

• Proceedings of the KWS Conference
• /
• 2008.05a
• /
• pp.23-23
• /
• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2008.06a
• /
• pp.685-686
• /
• 2008

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.837-839
• /
• 1995

This paper reports the current state of the intelligent mobile robot with flexible manipulators. Several technologies that have been developed and/or being developed are presented in this paper.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2011.06a
• /
• pp.1265-1266
• /
• 2011

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.628-632
• /
• 2003

An intelligent miniature humanoid robot system is designed and implemented as a platform for researching walking algorithm. The robot system consists of a mechanical robot body, a control system, a sensor system, and a human interface system. The robot has 6 dofs per leg, 3 dofs per arm, and 2 dofs for a neck, so it has total of 20 dofs to have dexterous motion capability. For the control system, a supervisory controller runs on a remote host computer to plan high level robot actions based on the vision sensor data, a main controller implemented with a DSP chip generates walking trajectories for the robot to perform the commanded action, and an auxiliary controller implemented with an FPGA chip controls 20 actuators. The robot has three types of sensors. A two-axis acceleration sensor and eight force sensing resistors for acquiring information on walking status of the robot, and a color CCD camera for acquiring information on the surroundings. As an example of an intelligent robot action, some experiments on playing soccer are performed.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.339-342
• /
• 1996

In this paper, the method for controlling PUMA robot using F/T sensor is described. In the part of the setup automation, robot is used. The F/T sensor is located at robot end-effector and various experiments are executed such as peg in hole, gripping objects, tool changing, etc.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.209-212
• /
• 2003

The following paper deals with a control problem of a mobile robot in home network environment. The home network causes the mobile robot to communicate with sensors to get the sensor measurements and to be adapted to the environment changes. We adopt the reinforcement learning scheme for the solution to the problem, and show some simulation results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.11a
• /
• pp.274-277
• /
• 2000

In this paper we propose new algorithms of path planning and obstacle avoidance for an autonomous mobile robot with vision system. Distance variation is included in path planning to approach the target point and avoid obstacles well. The fuzzy rules are also applied to both trajectory planning and obstacle avoidance to improve the autonomy of mobile robot. It is shown by computer simulation that the proposed algorithm is working well.