Jang Myung Lee

Localization of a mobile robot using the image of a moving object

This paper proposes a new approach for determining the location of a mobile robot using the image of a moving object. This scheme combines data from the observed position, using dead-reckoning sensors, and the estimated position, using images of moving objects captured by a fixed camera to determine the location of a mobile robot. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated robots position are derived. Since the equations are based on estimated position, measurement error may exist. However, the proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used for the estimation of the mobile robot location. The proposed approach is applied for a moving object on the wall to show the reduction of uncertainty in the determining of mobile robot location.

Partial Tracking Error Constrained Fuzzy Dynamic Surface Control for a Strict Feedback Nonlinear Dynamic System

As an extension of the conventional output constraint problem, this paper proposes the use of nonlinear dynamic surface control (DSC) combined with adaptive fuzzy logic control to constrain the partial tracking errors of strict feedback nonlinear dynamic systems with uncertainties. Transformation of the tracking errors into new virtual error variables is used to recursively design a DSC controller, and a careful selection of the controller design parameters ensures that partial state tracking errors are confined at all times within the prescribed bounds. The stability and boundedness of all closed-loop signals were confirmed using the Lyapunov theorem. The simulation results highlight the efficacy and utility of the proposed control scheme.

Balancing and Velocity Control of a Unicycle Robot Based on the Dynamic Model

This paper presents a dynamic-model-based control scheme for the balancing and velocity control of a unicycle robot. Unicycle robot motion consists of a pitch that is controlled by an in-wheel motor and a roll that is controlled by a reaction wheel pendulum. The unicycle robot lacks an actuator for yaw-axis control, which makes the derivation of the dynamics relatively simple although it may limit the motion control. The Euler-Lagrange equation is applied to derive the dynamic equations of the unicycle robot to implement dynamic speed control. To achieve real-time speed control, a sliding-mode control and a nonzero set-point linear quadratic regulator (LQR) are utilized to guarantee stability while maintaining the desired speed-tracking performance. In the roll controller, a sigmoid-function-based sliding-mode controller has been adopted to minimize switching-function chattering. An LQR controller has been implemented for pitch control to drive the unicycle robot to follow the desired velocity trajectory in real time using the state variables of pitch angle, angular velocity, wheel angle, and angular velocity. The control performance of the two control systems using a single dynamic model has been experimentally demonstrated.

Output-Tracking-Error-Constrained Robust Positioning Control for a Nonsmooth Nonlinear Dynamic System

An output-tracking-error-constrained dynamic surface control (DSC) is proposed for the robust output positioning of a multiple-input-multiple-output nonlinear dynamic system in the presence of both friction and deadzone nonsmooth nonlinearities. An error transformation method and simple barrier Lyapunov function are also proposed to ensure the prescribed output tracking performance and stability without requiring specific observations of the friction and deadzone parameters. In addition, a new adaptive cerebellar model articulation controller-echo state neural networks system is proposed to deal with an unknown nonlinear function to improve the positioning performance. The boundedness of the overall closed-loop signals and the prescribed performance constraints were guaranteed, and precise positioning performance was also ensured regardless of the effects of friction and deadzone. The proposed control scheme was evaluated by simulation and experiment.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions.

Adaptive Control of a Gyroscopically Stabilized Pendulum and Its Application to a Single-Wheel Pendulum Robot

This paper presents an adaptive decoupling control strategy for a gyroscopically stabilized pendulum. In the proposed model, the gyro moment acts directly on the pivot of the pendulum, the magnitude of which is restricted by gyroscopic precession. A decoupling algorithm based on virtual control is proposed to regulate the upright posture of the pendulum through gyroscopic precession. Virtual control is considered a control torque that acts on the pivot of the pendulum; it forms nonlinear mapping along with the precession command. Consequently, gyroscopic precession matches the stability condition of the pendulum well. In the control design, an adaptive disturbance estimation method based on a smooth saturation function is proposed to avoid the adverse effects of parametric uncertainties, mechanical vibrations, and system nonlinearities. Accurate estimation of unstructured disturbances is easily achieved by adaptively tuning the weight coefficient of the saturation function. The results of stability analysis, simulations, and experiments show the validity of the proposed pendulum model and adaptive decoupling control scheme.

Integrated wiring system for construction equipment

Advances in electronic technology have brought numerous changes in design of most types of construction equipment. Due to the electronic devices and electric loads, such as lamps and motors, a typical construction vehicle has many wires and connectors. The next phase of the changes is to focus on how to reduce these complex wires by using digital communications. This paper presents the development of an integrated wiring system for construction equipment. More specifically, an excavator that has more than 40 devices has been chosen in order to apply the concept of the integrated wiring system. After grouping electrical devices by their locations and functions, two communication controllers, i.e., an instrument controller and an engine-hydraulic controller, are defined. Two test controllers have been developed in order to prove the concept.

Internet-based Real-time obstacle avoidance of a mobile robot

In this research, a remote control system has been developed and implemented, which combines autonomous obstacle avoidance in real-time with force-reflective tele-operation. A teleoperated mobile robot is controlled by a local two-degrees-of-freedom force-reflective joystick that a human operator holds while he is monitoring the screen. In the system, the force-reflective joystick transforms the relation between a mobile robot and the environment to the operator as a virtual force which is generated in the form of a new collision vector and reflected to the operator. This reflected force makes the tele-operation of a mobile robot safe from collision in an uncertain and obstacle-cluttered remote environment. A mobile robot controlled by a local operator usually takes pictures of remote environments and sends the images back to the operator over the Internet. Because of limitations of communication bandwidth and the narrow viewangles of the camera, the operator cannot observe shadow regions and curved spaces frequently. To overcome this problem, a new form of virtual force is generated along the collision vector according to both distance and approaching velocity between an obstacle and the mobile robot, which is obtained from ultrasonic sensors. This virtual force is transferred back to the two-degrees-of-freedom master joystick over the Internet to enable a human operator to feel the geometrical relation between the mobile robot and the obstacle. It is demonstrated by experiments that this haptic reflection improves the performance of a tele-operated mobile robot significantly.

Finite-time sliding surface constrained control for a robot manipulator with an unknown deadzone and disturbance.

This paper presents finite-time sliding mode control (FSMC) with predefined constraints for the tracking error and sliding surface in order to obtain robust positioning of a robot manipulator with input nonlinearity due to an unknown deadzone and external disturbance. An assumed model feedforward FSMC was designed to avoid tedious identification procedures for the manipulator parameters and to obtain a fast response time. Two constraint switching control functions based on the tracking error and finite-time sliding surface were added to the FSMC to guarantee the predefined tracking performance despite the presence of an unknown deadzone and disturbance. The tracking error due to the deadzone and disturbance can be suppressed within the predefined error boundary simply by tuning the gain value of the constraint switching function and without the addition of an extra compensator. Therefore, the designed constraint controller has a simpler structure than conventional transformed error constraint methods and the sliding surface constraint scheme can also indirectly guarantee the tracking error constraint while being more stable than the tracking error constraint control. A simulation and experiment were performed on an articulated robot manipulator to validate the proposed control schemes.

Outdoor Localization for Quad-Rotor Using Extended Kalman Filter and Path Planning

This paper proposes a new technique that can be used to produce improved localization accuracy and to remove out the noises in sensing when the low-cost GPS/INS system has been used for a quad-rotor. The level of localization accuracy could be worse when the quad-rotor flies through the air by forming a curve. Also, the accuracy is influenced by the performance of GPS/INS system. The location data by the GPS/INS system include high frequency noises caused by various factors such as measurement noises and external disturbances. When the quad-rotor flies outdoor, it is possible to estimate the moving path for a short interval since the path can be assumed to be straight for a short interval. Therefore, the extended Kalman filter has been adopted to improve the localization accuracy. Also the global path can be more precisely estimated by fitting the location data obtained by the GPS/INS system to the planned path. Through the foregoing processes of the extended Kalman filter and path planning algorithm, the improved localization information can be obtained when the quad-rotor flies. Performance improvement of the proposed system has been verified based on various outdoor experiments.