• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.10
• /
• pp.1037-1043
• /
• 2011

Two-wheeled balancing mobile robots are currently controlled in terms of linear control methods without considering the nonlinear dynamical characteristics. However, in the high maneuvering situations such as fast turn and abrupt start and stop, such neglected terms become dominant and greatly influence the overall driving performance. This paper addresses the SDRE nonlinear optimal control method to take advantage of the exact nonlinear dynamics of the balancing robot. Simulation results indicate that the SDRE control outperforms LQR in the respect of transient performance and required wheel torques. A design example is suggested for the state matrix that provides design flexibility in the SDRE control. It is shown that a well-planned state matrix by reflecting the physics of a balancing robot greatly contributes to the driving performance and stability.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.9
• /
• pp.812-818
• /
• 2012

In this paper, we propose an asynchronous behavior control algorithm of the swarm robot for surrounding intruders when detected an intruder in a surveillance environment. The proposed method is divided into three parts: First, we proposed the method for the modeling of a state of the swarm robot. Second, we proposed an asynchronous behavior control algorithm for the surrounding an intruder by the swarm robot. Third, we proposed a control method for the collision avoidance with the swarm robot. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.10
• /
• pp.921-927
• /
• 2013

This paper presents a user interface for vision based indirect teaching of a robotic manipulator with Kinect and IMU (Inertial Measurement Unit) sensors. The user interface system is designed to control the manipulator more easily in joint space, Cartesian space and tool frame. We use the skeleton data of the user from Kinect and Wrist-mounted IMU sensors to calculate the user's joint angles and wrist movement for robot control. The interface system proposed in this paper allows the user to teach the manipulator without a pre-programming process. This will improve the teaching time of the robot and eventually enable increased productivity. Simulation and experimental results are presented to verify the performance of the robot control and interface system.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.513-518
• /
• 1998

In this paper, a robust fault-tolerant control scheme for robot manipulators overcoming actuator failures is presented. The joint(or actuator) fault considered in this paper is the free-swinging joint failure and causes the loss of torque on a joint. The presented fault-tolerant control framework includes a normal control with normal(non-failed) operation, a fault detection and a fault-tolerant control to achieve task completion. For both no uncertainty case and uncertainty case, a stable normal con-troller and an on-line fault detection scheme are presented. After the detection and identification of joint failures, the robot manipulator becomes the underactuated robot system with failed actuators. A robust adaptive control scheme of robot manipulators with the detected failed-actuators using the brakes equipped at the failed(passive) joints is proposed in the presence of parametric uncertainty and external disturbances. To illustrate the feasibility and validity of the proposed fault-tolerant control scheme, simulation results for a three-link planar robot arm with a failed joint are presented.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.4
• /
• pp.290-296
• /
• 2005

This paper presents the implementation of a crack tracking mobile robot. The crack tracking robot is built for tracking cracks on the pavement. To track cracks, crack must be detected by laser and camera sensors. Laser sensor projects laser on the pavement to detect the discontinuity on the surface and the camera captures the image to find the crack position. Then the robot is commanded to follow the crack. To detect crack position correctly, neural network is used to minimize the positional errors of the captured crack position obtained by transformation from 2 dimensional images to 3 dimensional images.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.4
• /
• pp.330-336
• /
• 2005

An intelligent control method is proposed for control of rigid robot manipulators which achieves exponential tracking of repetitive robot trajectory under uncertain operating conditions such as parameter uncertainty and unknown deterministic disturbance. In the learning controller, exponentially stable learning algorithms are combined with stabilizing computed error feedforward and feedback inputs. It is shown that all the error signals in the learning system are bounded and the repetitive robot motion converges to the desired one exponentially fast with guaranteed convergence rate. An engineering workstation based control system is built to verify the effectiveness of the proposed control scheme.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.9
• /
• pp.868-875
• /
• 2006

The localization is one of the most important issues for mobile robot. This paper describes a novel localization system for the development of a location sensing network. The system comprises wirelessly controlled infrared landmarks and an image sensor which detects the pixel positions of infrared sources. The proposed localization system can operate irrespective of the illumination condition in the indoor environment. We describe the operating principles of the developed localization system and report the performance for mobile robot localization and navigation. The advantage of the developed system lies in its robustness and low cost to obtain location information as well as simplicity of deployment to build a robot location sensing network. Experimental results show that the developed system outperforms the state-of-the-art localization methods.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.3
• /
• pp.349-359
• /
• 1998

A robot control scheme for specific application a line-tracking system is newly presented. To improve the performance of line-tracking, robot arm dynamics and torque constraints are incorporated into the control scheme. The tracking problem for the workpiece on a variable-speed conveyor is formulated as an optimal tracking problem with specific criteria. Dividing the conveyor speed into the nominal term and the perturbed term, a two-stage control strategy is employed to cope with the nonlinearity and uncertainty of the robot-conveyor system. Simulation results are given to verify good tracking performance with fast cycle time and high accuracy in a robotic workcell.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.2
• /
• pp.226-234
• /
• 1998

The concept of dynamic tracking line is proposed as the feasible tracking region for a robot in a robot-conveyor system, which takes the conveyor speed into consideration. This paper presents an effective method to identify the dynamic tracking line in a robotic workcell. The maximum line speed of a robot is derived in an analytic form using the parameterized dynamics and kinematics of the manipulator, and some of its properties are established mathematically. The identification problem of the dynamic tracking line is then formulated as a root-solving problem for a single-variable equation, and solved by using a simple numerical technique. Finally, numerical examples are presented to demonstrate the methodology and its applications in workspace specification.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.10
• /
• pp.888-894
• /
• 2005

In this paper, experimental studies of balancing a pendulum mounted on a wheeled drive mobile robot and its position control are presented. Main PID controllers are compensated by a neural network. Neural network learning algorithm is embedded on a DSP board and neural network controls the angle of the pendulum and the position of the mobile robot along with PID controllers. Uncertainties in system dynamics are compensated by a neural network in on-line fashion. Experimental results show that the performance of balancing of the pendulum and position tracking of the mobile robot is good.