Search

This paper proposes positioning and trajectory tracking for Caterpillar Vehicles (CVs) in unknown environments. To do these tasks, the following are performed. Firstly, a system modeling of the Caterpillar Vehicle is presented. Secondly, solving the complicated tracking control problem in unknown environments is a challenging mission. Therefore, to guarantee the Caterpillar Vehicle system to be strong robustness against external disturbances in the unknown environments, a MIMO robust servo controller for tracking the desired trajectory is designed by using a Linear Shift Invariant Differential (LSID) operator. The CVs are able to accomplish various tasks in dangerous places where workers cannot enter. Thirdly, the positioning of the CV can be obtained using a Simultaneous Localization and Mapping (SLAM) method. This paper develops perfectly the SLAM algorithm for positioning of the CV based on laser sensor Lidar. The main advantage of this method is that it does not need to use more landmarks. Landmarks can be obtained from the unknown environment. Thus, the CV can work even in unknown environments and unsafe places. Finally, to verify the effectiveness of the proposed MIMO robust servo controller and the SLAM positioning algorithm, the experimental results are presented. The experimental results demonstrate the adequate tracking performance of the proposed MIMO robust servo controller in the unknown environment.

This paper proposes a servo system designed for speed control of AC induction motors using polynomial differential operator to track more complicated types of reference speed and disturbance such as step, ramp, parabola, etc. To do this task, the followings are done. First, modeling for an induction motor is introduced and is linearized at equilibrium points using Taylor’s series. Second, observer is designed to estimate flux, and an extended system incorporating the internal model principle to construct the servo system is derived using polynomial differential operator in case that the types of reference inputs are polynomials. Third, a state feedback control law for the servo system to track the given reference input is designed. To implement the proposed controller and servo system, a control system is constructed for speed control of 1.5 Kw AC induction motor. The simulation and experimental results are conducted to verify the effectiveness and the applicability of the proposed controller compared to the conventional PID controller and MRAC controller for more complicated higher order types of the references and disturbance such as step, ramp, parabola, etc.

This paper proposes a fish contour detection method using a local kernel regression method. To do this task, the followings are done. Firstly, 3D depth map of a fish is obtained by using Kinect camera sensor. Secondly, edge of the fish in 3D depth map is transformed into numerous points. Thirdly, all information is removed except the edge points. However, recognition points for recognizing the fish are appropriately left because there are only points left to distinguish between background and fish. Fourthly, the points are recognized as contour of the fish by using the local kernel regression method. Finally, experiment results using Kinect camera sensor are shown to verify the validity of the proposed method compared to Canny method.

This paper proposes a visual servoing controller design based on Barrier Lyapunov function for a picking system. Visual servoing uses feedback data provided by the camera to control the movement of a picking system in a closed loop system. Visual servoing requires an object in the field of view of the camera in order to control the picking system. To improve the visual servoing controller, the image-based visual servoing and the position-based visual servoing are presented. To apply this method an offline trajectory is developed to perform the image-based visual servoing and the position-based visual servoing tasks for the picking system. Two different control approaches i.e. the visual servoing controller with the limit orientation using the Barrier Lyapunov function and the visual servoing controller with a quadratic Lyapunov function are presented. The proof of asymptotic stability is presented and simulation results from two visual servoing controllers are presented to verify the effectiveness of the proposed controller.

This paper presents positioning and obstacle avoidance of Automatic Guidance Vehicle (AGV) in partially known environment. To do this task, the followings are done. Firstly, the system configuration of AGV is described. Secondly, mathematical kinematic modeling of the AGV is presented to understand its characteristics and behavior. Thirdly, the Simultaneous Localization and Mapping (SLAM) algorithm based on the laser measurement system and encoders is proposed. The encoders are used for detecting the motion state of the AGV. In a slippery environment and a high speed AGV condition, encoder positioning method generates big error. Therefore, Extended Kalman Filter (EKF) is used to get the best position estimation of AGV by combining the encoder positioning result and landmark positions obtained from the laser scanner. Fourthly, to achieve the desired coordinate, D* Lite algorithm is used to generate a path from the start point to the goal point for AGV and to avoid unknown obstacles using information obtained from laser scanner. A backstepping controller based on Lyapunov stability is proposed for tracking the desired path generated by D* Lite algorithm. Finally, the effectiveness of the proposed algorithms and controller are verified by using experiment. The experimental results show that the AGV successfully reaches the goal point with an acceptable small error.

This paper presents a new type of four wheel independent steering automatic guided vehicle (4WIS-AGV) for carrying heavy baggage and proposes a controller for the 4WIS-AGV to track reference trajectories. To do this task, the followings are done. Firstly, a 4WIS-AGV is designed and manufactured for experimental purpose. Secondly, a kinematic modeling for the 4WIS-AGV is introduced based on a single track vehicle model. Thirdly, based on the modeling, a controller is designed based on Backstepping method for the 4WIS-AGV to track reference trajectories. Fourthly, a control system is developed using industrial PC and AVR ATmega128 microcontrollers to implement the designed controller. Finally, simulations and experiments are conducted to verify the effectiveness and performances of the proposed controller in tracking two types of reference trajectories: a trajectory with sharp edges for parallel steering maneuver and a circular trajectory for zero-sideslip maneuver. The results show that the proposed controller can make the 4WIS-AGV track the trajectory with sharp edges and the circular trajectory very well.

This paper proposes two measurement methods for injured rate of fish surface using color image segmentation method based on K-means clustering algorithm and Otsu’s threshold algorithm. To do this task, the following steps are done. Firstly, an RGB color image of the fish is obtained by the CCD color camera and then converted from RGB to HSI. Secondly, the S channel is extracted from HSI color space. Thirdly, by applying the K-means clustering algorithm to the HSI color space and applying the Otsu’s threshold algorithm to the S channel of HSI color space, the binary images are obtained. Fourthly, morphological processes such as dilation and erosion, etc. are applied to the binary image. Fifthly, to count the number of pixels, the connected-component labeling is adopted and the defined injured rate is gotten by calculating the pixels on the labeled images. Finally, to compare the performances of the proposed two measurement methods based on the K-means clustering algorithm and the Otsu’s threshold algorithm, the edge detection of the final binary image after morphological processing is done and matched with the gray image of the original RGB image obtained by CCD camera. The results show that the detected edge of injured part by the K-means clustering algorithm is more close to real injured edge than that by the Otsu’ threshold algorithm.

This paper presents an implementation and experimental validation of trajectory tracking and fault detection algorithm for sensors and actuators of Automatic Guided Vehicle (AGV) system based on multiple positioning modules. Firstly, the system description and the mathematical modeling of the differential drive AGV system are described. Secondly, a trajectory tracking controller based on the backstepping method is proposed to track the given trajectory. Thirdly, a fault detection algorithm based on the multiple positioning modules is proposed. The AGV uses encoders, laser scanner, and laser navigation system to obtain the position information. To understand the characteristics of each positioning module, their modeling are explained. The fault detection method uses two or more positioning systems and compares them using Extended Kalman Filter (EKF) to detect an unexpected deviation effected by fault. The pairwise differences between the estimated positions obtained from the sensors are called as residue. When the faults occur, the residue value is greater than the threshold value. Fault isolation is obtained by examining the biggest residue. Finally, to demonstrate the capability of the proposed algorithm, it is applied to the differential drive AGV system. The simulation and experimental results show that the proposed algorithm successfully detects the faults when the faults occur.

Determination of injury rate on fish surface is one of the major cause for increasing quality of fish on the markets. Detecting injury fishes manually is hard work with low efficiently. An image processing method is usually considered to do this work as an online selecting method of injury area. The injury area segmentation of fish image is based on color features with Fuzzy C-means clustering and L*a*b* color space. Although there are many different color spaces. CIE L*a*b* color space of them is most used for detecting fish injury due to its uniform color distribution and is closest to the one human eye. Generally, a fish injury image has overlapped data with fish body image. The K-means clustering algorithm cannot give the good solution to segment whether pixels of the overlapped data belong to fish body or injury area. To solve this problem, this paper is to present the good solution for segmentation of fish injury image with the overlapped data from the fish body image and determine injury rate on fish surface based on Fuzzy C-means clustering and L*a*b* color space using ZED stereo camera. The proposed image processing method is tested on fishes. The experimental results show that the injury rate measured using the proposed image processing method is close to the real injury rate.

In May 2015, Middle East respiratory syndrome coronavirus infection was laboratory confirmed in South Korea. Patients were a man who had visited the Middle East, his wife, and a man who shared a hospital room with the index patient. Rapid laboratory confirmation will facilitate subsequent prevention and control for imported cases.

Based on basic properties of L*A*B* color space, this paper proposes a new approach of 2D image processing which is used for measurement of injury rate on fish by a modified K-means clustering algorithm and Otsu’s threshold algorithm. Then, experimental results of the proposed method are compared to the results of a manual threshold method on L*A*B* color space. To do this issue, the following tasks are done. Firstly, an original color image is transferred into L*A*B color space. Secondly, channel “a” is separated from L*A*B* color space image. Thirdly, the value of channel “a” is adjusted by changing the contrast algorithm. Fourthly, the modified K-means clustering algorithm on a new channel “a” image is applied to define and divide data elements into different groups. Fifthly, Gaussian Filter is used to filter the random “noises” in shape of injury and fish images. Sixthly, Otsu’s threshold algorithm is used to transfers the filtered images into binary images. Seventhly, final images are obtained after filtering the rest of “noises” by morphological processing. Finally, the areas of injury and fish shapes are obtained by counting pixels on both of the final binary images. The experiment results show that the proposed new approach is closer to the real injury and injury rate on fish than the results of the manual threshold method on L*A*B color image.

This paper proposes recognition and grasping objects from 3D environment by combining depth and color stereo image in the mobile picking robot system. To do this task, the followings are done. Firstly, an image processing system including Kinect camera sensor is described. Secondly, RGB color map and new depth map for image inpainting are obtained using Kinect SDK mapping function to align RGB image with depth image. Thirdly, the new depth map are segmented to distinguish between the image background and the objects that should be recognized. The feature colours are generated based on colour histograms. Euclidean distance is used to measure the similarity between the feature vectors computed from the colour image and the feature vectors stored in a database. Fourthly, by converting RGB map and new depth map into 3D point clouds, an algorithm for localizing handle-like grasp affordances is proposed. The main idea is to search the point cloud for neighborhoods that satisfy handle-like grasp affordances and can be grasped by the end-effector of the manipulator. Finally, the effectiveness of the proposed algorithms is verified by using experiment. The experimental results show that the mobile picking robot successfully detects an object and finds its grasping points with an acceptable small error.

This paper proposes determination of the fish surface area and volume using ellipsoid approximation method applied for image processing based on two views of fish images. The fishes are considered as ellipsoid shapes on three view sides that appropriate analytical models for their surface and volume estimation. To do this task, the followings are done. Firstly, mathematical modeling of surface area and volume of ellipsoid analytically are presented. Secondly, ellipsoid shape is segmented to determine surface area and volume for computation. Finally, surface area and volume of fish are measured by image processing technique. The surface area and volume computed are compared with analytical and experimental results.

This paper is about control of Automated Guided Vehicle for path following using fuzzy logic controller. The Automated Guided Vehicle is a tricycle wheeled mobile robot with three wheels, two fixed passive wheels and one steering driving wheel. First, kinematic and dynamic modeling for Automated Guided Vehicle is presented. Second, a controller that integrates two control loops, kinematic control loop and dynamic control loop, is designed for Automated Guided Vehicle to follow an unknown path. The kinematic control loop based on Fuzzy logic framework and the dynamic control loop based on two PID controllers are proposed. Simulation and experimental results are presented to show the effectiveness of the proposed controllers.

Autonomous Guided Vehicle Systems (AGVs) are used to transport goods and products in manufacturing fields where navigation can be done in a structured environment. In order to track the given trajectory, a tracking control based on Lyapunov stability theory is introduced. The use of the nonlinear Lyapunov technique provides robustness for load disturbance and sensor noise. To apply Lyapunov's theorem, the kinematic model of AGV is given. To recognize its position in indoor environment, in this paper, a laser sensor device NAV200 is used to detect the AGV position in real-time. For simulation and experiment, software and hardware are described. The AGV consists of 4 wheels with two passive wheels and two driving wheels. A controller is developed based on industrial computer. The effectiveness of the proposed controller is proved by simulation and experimental results. [AGV Trajectory Control, Laser Sensor Navigation]

Modified-model reference adaptive controller (M-MRAC) for belt conveyors of induction conveyor line in the presence of saturated inputs and bounded disturbances is proposed in this paper. In this controller, M-MRAC architecture is combined with robust e-modification adaptive laws for the MIMO linear system with unknown bounded disturbances. For the M-MRAC system, adaptation rate can increase largely without generating high frequency oscillation in control input signal and e-modification update laws prevents a drift of estimate parameters in the presence of the bounded disturbance. Moreover, an auxiliary system is introduced for compensating the error dynamics of the MIMO linear system when the saturation input occurs. Therefore, the steady state error is guaranteed around bounded range when a saturated input error does not equal to zero. Finally, the simulation results are shown to verify the effectiveness and the performance of the proposed controller for the MIMO linear system with the bounded disturbance and saturated input and a conventional MRAC controller.

Motion planning, such as mobile manipulation, must not only be able to move safety through their environments, but also be able to manipulate objects in their environments. This paper proposes localization and path planning for a mobile robot (MR) in a picking robot system using Kinect camera in a partially known environment. A Kinect RGB and depth camera is utilized to recognize objects for obstacle avoidance and path planning. To do this task, the followings are done. Firstly, the system configuration of MR is described. Secondly, mathematical kinematic modeling of the MR in the picking robot system is presented. Thirdly, an object detection algorithm based on the Kinect camera is proposed to detect landmark. Extended Kalman Filter (EKF) is used to get the best localization estimation of the MR by combining the encoder positioning result and landmark positions obtained from the Kinect camera. Fourth, D* Lite algorithm is used to generate a path from the start point to the goal point for MR and to avoid unknown obstacles using information obtained from Kinect camera. A controller design for the MR to track the trajectory generated by the D* algorithm based on backstepping method is proposed. Finally, the effectiveness of the proposed algorithms and controller is verified by using experiment. The experimental results show that the MR successfully reaches the goal point with an acceptable small error.

This paper proposes a method for measuring fish-body wound depth using a depth map inpainting method. To do this task, the following are done. Firstly, an image processing system including Kinect V2 camera sensor is described. The RGB image and the depth map are obtained by Kinect V2 camera sensor for Windows. Secondly, RGB color map and new depth map for image inpaiting are obtained using Kinect SDK mapping function to align RGB image with depth image. The obtained new depth map still has some noise problems and some depth information are lost. Thirdly, to remove the new depth map noise, a depth map inpainting method is proposed. Fourthly, binarization process is done directly after inpainting the new depth map by the proposed depth map inpainting method. Fifthly, A measurement method to calculate the fish body wound depth data is proposed. Finally, the experimental results are shown to verify the effectiveness of the proposed method.

This paper presents a vision-based object following four wheel independent steering automatic guided vehicle (4WIS-AGV) system using Kinect camera sensor. To do this task, the following steps are executed. Firstly, an image processing is done for object detection using Kinect camera sensor. A candidate colored object is detected using color-based object detection method and its position in local coordinates is obtained. NAV200 navigation sensor is used to obtain global position of the detected object and the 4WIS-AGV. Secondly, the position of the detected moving object is estimated using Kalman filter algorithm. Kalman filter is used to estimate the global position of the detected moving object. Thirdly, a backstepping controller based on Lyapunov stability is proposed to achieve object following task. Finally, the effectiveness of the proposed system is verified by using simulation and experimental results. The results show that the proposed controller makes the 4WIS-AGV follow the detected moving object well with an acceptable error.

This paper proposes a tracking controller for obstacle avoidance of a quadruped robot using potential functions method. The followings are done for this task. At first, a ceiling-mounted camera system is installed for image processing. The goal point and obstacles are separated and recognized by a color recognition method. Second, a path planning algorithm using potential functions method is proposed to generate the path to avoid obstacles and to plan a path for the quadruped robot to reach from start point to goal point. Third, a quadruped robot is chosen as the mobile platform for this study and the kinematic model for the robot is presented. Fourth, a tracking controller is designed for the quadruped robot to track the trajectory based on the backstepping method using Lyapunov function. Finally, the simulation results are presented to show the effectiveness of the proposed trajectory planning algorithm and the tracking controller. [Keywords — Path tracking ; back stepping ; obstacles avoidance ; potential functions ; quadruped robot ] .

In this paper, stabilization of a 2-degrees-of-freedom (2-DOF) omnidirectional mobile inverted pendulum (OM-IP) is studied. The OM-IP consists of the rod that rotates around a rotary point of a universal joint which is connected at the center of the omnidirectional mobile platform (OMP). For ease of analysis, the OM-IP is decoupled into two subsystems: a 2-DOF inverted pendulum (IP) and an OMP. The IP is a rod that rotates around a universal joint with 2-DOF. The OMP is a body consisting of disk and three omnidirectional wheels that moves on plane and keeps the rod in balance. Dynamic modeling of the 2-DOF OM-IP is presented. From the dynamic equa- tion, an adaptive backstepping control method is proposed to keep the rod in balance. Update law is presented as differential equation of an unknown parameter when the distance from the center of gravity of the rod to the rotary point on the OMP is unknown. Stability of the adaptive controller is proven by using Lyapunov function. Simulation and experimental results show the effectiveness of the proposed controller.

This paper proposes a tracking control method for a three-wheeled omnidirectional manipulator system (OMMS) with disturbance and friction. The OMMS is separated into two subsystems, a three-wheeled omnidirectional mobile platform (OMP) and a selective compliant articulated robot for assembly (SCARA) type of manipulator. Therefore, two controllers are designed to control the OMP and the manipulator system. Firstly, based on a kinematic modeling of the manipulator, a kinematic controller (KC), combined with an integral sliding mode controller (ISMC), is designed for the end-effector of the manipulator to track a desired trajectory with the desired angular velocity vector of links. Secondly, a differential sliding mode controller (DSMC) based on a dynamic modeling of the OMP with force external disturbances is proposed to obtain control inputs moving the OMP so that the manipulator tracks the desired posture without singularity. The system stability is proven using Lyapunov stability theory. The simulation and experimental results are presented to illustrate the effectiveness of the proposed controllers in the presence of disturbance and friction.

In this paper, a differential sliding mode tracking controller (DSMC) using voltage input is designed for trajectory tracking of the three-wheeled omnidirectional mobile platform (OMP) based on its dynamic modeling with disturbances. First, a tracking error vector is defined, and then a differential sliding surface vector is chosen. A control law is obtained by using Lyapunov direct method with backstepping technique. The control law stabilizes the sliding surface vector and makes the tracking error vector go to zero asymptotically. To implement the designed controllers, a control system is developed based on PIC microcontroller. A camera sensor and encoders are used. The simulation and experiment results are presented to illustrate effectiveness of the proposed controller.

This paper describes a new method for a digital gas metal arc welding (GMAW) system. The GMAW system is an arc welding process that incorporates the GMAW power source (PS-GMAW) with a wire feed unit (WFU). The PS-GMAW requires an electric power of constant voltage. A constant magnitude is maintained for the arc current by controlling the wire-feed speed of the WFU. A mathematical model is derived, and a self-tuning fuzzy proportional-integral-derivative (PID) controller is designed and applied to control the welding current. The electrode wire feeding mechanism with this controller is driven by a DC motor, which can compensate for both the molten part of the electrode and undesirable fluctuations in the arc length during the welding process. By accurately maintaining the output welding current and welding voltage at constant values during the welding process, excellent welding results can be obtained. Simulation and experimental results are shown to prove the effectiveness of the proposed controller.

This paper proposes a controller design for an omnidirectional mobile platform (OMP) with three wheels using backstepping control. A kinematic model and dynamic model of the system are presented. Based on the dynamic modeling, a backstepping controller is designed to stabilize the OMP when following a desired path. The controller is designed based on a backstepping control theory. It includes two steps: first, a virtual state and a stability function are introduced. Second, Lyapunov functions for the system are chosen and an equation for the virtual control that makes the system stabile is obtained. The system stability is guaranteed by the Lyapunov stability theory. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed controller.

This paper proposes the design and development results of a new quadruped robot. The proposed new quadruped robot has a couple of advantages of flexible locomotion. The quadruped robot is designed and modeled based on a new concept that is the structure model with three segments of quadruped legs. New leg configuration with the simplified operation of four hip actuators is introduced. The posture of the new quadruped robot is more similar to the posture of dog than that of the previous quadruped robots. The objective of this paper is to develop a quadruped robot, which can walk and run in a trot gait with a simple PID controller. Numerical simulation and experimental results are shown to prove the locomotion performance of the proposed controller for the proposed quadruped robot.

In this paper, a control scheme that combines a kinematic controller and a sliding mode dynamic controller with external disturbances is proposed for an automatic guided vehicle to track a desired trajectory with a specified constant velocity. It provides a method of taking into account specific mobile robot dynamics to convert desired velocity control inputs into torques for the actual mobile robot. First, velocity control inputs are designed for the kinematic controller to make the tracking error vector asymptotically stable. Then, a sliding mode dynamic controller is designed such that the mobile robot’s velocities converge to the velocity control inputs. The control law is obtained based on the backstepping technique. System stability is proved using the Lyapunov stability theory. In addition, a scheme for measuring the errors using a USB camera is described. The simulation and experimental results are presented to illustrate the effectiveness of the proposed controller.

This paper analyses and compares the performance of L*A*B* and HSV color spaces and applies them to calculate the injury rate on fish. To do these issues, the following steps are done. An original image is transformed into L*A*B and HSV color spaces. A channel “a” is separated from L*A*B* color space. In channel a, a formula to adjust “channel a value” is proposed to realize the shapes of injury on fish clearly and a new channel a is obtained by adjusting the channel a. The new channel “a” is converted into injury binary image by manual threshold. Otsu’s method is applied converted the original channel a image of fish shape into binary image. Finally, by calculating the number of pixels of areas of shape and total injury of fish, the injury rate is calculated. The steps of image processing of HSV color space is similar to L*A*B* color space. The proposed process are tested on fish.

This paper presents a relatively new method for achieving better welding results of gas metal arc welding (GMAW) system by using a decentralized control method. The GMAW system is an arc welding process which incorporates the power source of GMAW (PS-GMAW) with the wire feed unit (WFU). In this paper, the GMAW system is considered as two separated subsystems, those are PS-GMAW and the WFU. The mathematical modeling of PS-GMAW and WFU are presented. Based on two subsystems, a sliding mode controller is designed and applied to control the WFU meanwhile a proportional controller is designed and applied to control the PS-GMAW. Furthermore, two decentralized controllers have to be designed to control the welding arc of GMAW, be stable and control the output welding current and welding voltage for tracking the constant setting values accurately during the welding process, respectively. The simulation and experimental results are presented to show the effectiveness of the proposed controllers.

This paper presents a Kinect camera sensor-based object tracking and following system for the four wheel independent steering automatic guided vehicle (4WIS-AGV) using Kalman filter and backstepping control method. To accomplish this task, the following steps are executed: Firstly, a blue colored object is detected by the Kinect camera sensor using a color-based object detection method and its center coordinates inside the RGB image frames are obtained. The global position coordinates of the detected object and the 4WIS-AGV are obtained using Kinect depth data and NAV200 navigation system. Secondly, a Kalman filter is used to estimate the global position and velocity coordinates of the detected moving object. Thirdly, a backstepping control method using Lyapunov function is adopted for the 4WIS-AGV to perform the object following task. Finally, simulation and experiment are performed to verify the effectiveness of the proposed system. The results show that the 4WIS-AGV with Kinect camera sensor can follow the moving object well with the designed controller.

This paper presents a decentralized motion control method of welding mobile manipulators which use for welding in many industrial fields Major requirements of welding robots are accuracy, robust, and reliability so that they can substitute for the welders in hazardous and worse environment To do this, the manipulator has to take the torch tracking along a welding trajectory with a constant velocity and a constant heading angle, and the mobile-platform has to move to avoid the singularities of the manipulator In this paper, we develop a kinematic model of the mobile-platform and the manipulator as two separate subsystems With the idea that the manipulator can avoid the singularities by keeping its initial configuration in the welding process, the redundancy problem of system is solved by introducing the platform mobility to realize this idea Two controllers for the mobile-platform and the manipulator were designed, respectively, and the relationships between two controllers are the velocities of two subsystems Control laws are obtained based on the Lyapunov function to ensure the asymptotical stability of the system The simulation and experimental results show the effectiveness of the proposed controllers

This paper presents a development result for image processed tracking system of multiple moving objects based on Kalman filter and a simple window tracking method. The proposed algorithm of foreground detection and background adaptation (FDBA) is composed of three modules: a block checking module (BCM), an object movement prediction module (OMPM), and an adaptive background estimation module (ABEM). The BCM is processed for checking the existence of objects. To speed up the image processing time and to precisely track multiple objects under the object’s mergence, a concept of a simple window tracking method is adopted in the OMPM. The ABEM separates the foreground from the background in the reset simple tracking window in the OMPM. It is shown through experimental results that the proposed FDBA algorithm is robustly adaptable to the background variation in a short processing time. Furthermore, it is shown that the proposed method can solve the problems of mergence, cross and split that are brought up in the case of tracking multiple moving objects.

This paper introduces omni-directional walking control of a six-legged robot (6LR). The 6LR consists of its body, six legs with four links and four rotational joints. The followings are done for this task. First, the walking gait of the 6LR is chosen. Second, modeling for one leg with four links and four rotational joints of the 6LR is proposed. It is difficult and complex to get the angles of four rotational joints in the case of using inverse kinematics. To solve this problem, differential kinematics algorithm is used to generate omni-directional walking trajectory of a leg based on back-stepping control using Lyapunov stability. Finally, simulation results for walking motion of one leg of the 6LR are shown to prove the effectiveness and applicability of the proposed controller.

In this paper, a sensorless vector control method is introduced where rotor speed is estimated based on extended Kalman filter (EKF). The EKF is a recursive optimum stochastic state estimator. The proposed EKF is designed to obtain a small estimation speed error in both transient and steady state over a wide speed range. A major challenge at very low and zero speed is the lost coupling effect from the rotor to the stator, which makes the information on rotor variables unobservable on the stator side. To solve this problem, in the proposed EKF, the load torque and the rotor speed with unmeasurable information are estimated simultaneously. The rotor speed is considered via the equation of motion and the estimation of load torque, on the other hand, is performed as a constant parameter. Hardware and software for experiment of the AC induction motor drive are introduced. The experimental results are presented to show the effectiveness of the proposed system.

This paper proposes a tracking controller for obstacle avoidance of an omni-directional mobile vehicle (OMV) using potential function method through a ceiling-mounted camera system. To do this task, the followings were done. At first, for image processing, a ceiling-mounted camera system was installed to get images. The goal point and obstacles were separated and recognized by a color recognition method. Second, potential function method was proposed to generate the shortest path to avoid obstacles from the start point to the goal point. The mobile platform is a mecanum wheel omni-directional vehicle. Third, the tracking controller is designed for the OMV to track a trajectory generated by a path planning algorithm based on the backstepping method using Lyapunov function. Finally, the simulation results were presented to show the effectiveness of the proposed trajectory planning algorithm and tracking controller for obstacle avoidance of the OMV.

This paper introduces a path tracking controller for six legs control and omni-directional gaits of hexapod robot. The hexapod robot consists of its body and six legs. A leg has three links and three rotational joints. One leg is designed by forward kinematic for mathematic modeling. Path tracking controller is developed based on back-stepping control using Lyapunov stability and tracking reference trajectory of one leg with smooth and uniform velocity. A hardware control system of the hexapod robot is developed based on DSP TMS320F28335 micro-controller and AX-12A servo motors with half duplex communication. The simulation and experimental results are shown to prove the effectiveness and applicability of the applied controller. For experiment, we apply tripod gait to the hexapod robot.

This paper introduces a tracking controller for Automatic Guided Vehicles (AGV) to track a desired trajectory. The use of the nonlinear Lyapunov technique provides robustness for load disturbance and sensor noise. Based on kinematic model, a trajectory tracking controller of AGV is proposed. System stability is verified by Lyapunov stability. A laser sensor device NAV200 is used to detect the AGV position in door environment in real-time. For simulation and experiment, software and hardware are described. The AGV consists of 4 wheels with two passive wheels and two driving wheels. A controller is developed based on industrial computer. The effectiveness of the proposed controller is proved by simulation and experimental results.

In this paper, we present a navigation control algorithm for Automatic Guided Vehicles (AGV) that move in industrial environments including static and moving obstacles using D* algorithm. This algorithm has ability to get paths planning in unknown, partially known and changing environments efficiently. To apply the D* search algorithm, the grid map represent the known environment is generated. By using the laser scanner LMS-151 and laser navigation sensor NAV-200, the grid map is updated according to the changing of environment and obstacles. When the AGV finds some new map information such as new unknown obstacles, it adds the information to its map and re-plans a new shortest path from its current coordinates to the given goal coordinates. It repeats the process until it reaches the goal coordinates. This algorithm is verified through simulation and experiment. The simulation and experimental results show that the algorithm can be used to move the AGV successfully to reach the goal position while it avoids unknown moving and static obstacles. [Keywords — navigation control algorithm; Automatic Guided Vehicles (AGV); D* search algorithm ]

A nonlinear constrained model predictive control (NCMPC) method is presented for the control of the dissolved oxygen in a bio-reactor system using Hammerstein model. The control of dissolved oxygen as output is accomplished by adjusting the stirrer speed as input. The proposed controller is compared with the Nonlinear Model Predictive Control(NMPC) method without input constraints. The simulations and experiments are implemented. A control system based on microprocessor PIC16F877 is developed to implement the experiments. The simulation and experimental results show that the performance of the input stirrer speed with input constraints is better than that without input constraints. The effectiveness of the proposed controller is shown through simulations under the known disturbance and variable set-point tracking.

This paper considers the control system design for a mobile inverted pendulum via sliding mode technique. Firstly, a linear system is described in order to facilitate the development of an efficient control system. Secondly, sliding mode controllers are developed for stabilizing and tracking this system. Thirdly, the controllers have been implemented on a PIC microcontroller board. Additionally, the simulations were given to prove the validity of the proposed controllers.

This paper presents development results of an active tension system for replacing a passive tension system on a brushless direct current coil winding machine to improve the performance of the winding machine. Firstly, a comparison in winding procedure between circular and non-circular cross-section winding processes is considered to evaluate and design the proposed active tension system. Secondly, to reduce the fluctuation of wire tension in the winding process, a wire accumulator including pneumatic cylinder, servo valve and spring is used. Thirdly, in order to control the system, a fuzzy logic controller with three inputs and two outputs is employed. Finally, experimental results show that the winding machine equipped with the active tension system not only has ability to operate at high speed without wire broken but also decreases coil size in dimension.

This paper proposed a sliding mode control method for a two-wheel welding mobile manipulator to track a smooth 3D curved welding path. To design a tracking controller, the tracking errors are defined between the welding point of the torch and the reference point moving at a specified constant welding speed on the welding path. A sliding surface is set up and a control law is proposed for stabilization of the sliding surface. The simulations are performed to show the effectiveness of the proposed controller.