Trong Hai Nguyen

Mobile Robot Localization and Path Planning in a Picking Robot System Using Kinect Camera in Partially Known Environment

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.

Recognition and Grasping Objects from 3D Environment by Combining Depth and Color Stereo Image in the Mobile Picking Robot System

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.

Study on Hybrid Method for Efficiency Optimization of Induction Motor Drives

This paper proposes a new hybrid method for efficiency optimization of induction motor drives. To do this task, the followings are done. Firstly, the induction motor drive with 3 phases is modeled by using copper loss and core loss to find out the optimal efficiency of the power losses. Secondly, golden section technique is used to optimize the drive efficiency by searching for an optimal value according to the reference rotor flux current. In this way, the electrical input power of the system can also be minimal. Finally, the improved algorithm is proposed to enhance the system response speed and reduce torque ripple. The simulation is done to validate the proposed algorithm. The simulation results show that the proposed algorithm can be better than a convention method such as loss model control (LMC) and search control (SC) in terms of lower torque ripple and higher response speed.

Servo Controller Design for Speed Control of BLDC Motors Using Polynomial Differential Operator Method

This paper proposes a servo controller design method for speed control of Brushless DC (BLDC) motors using polynomial differential operator method. To do this task, the followings are done. Firstly, modeling for a BLDC motor is introduced and an extended system incorporating the internal model principle to construct the servo system is shown using polynomial differential operator in case that the types of reference inputs are differential polynomials. Secondly, a state feedback control law for the servo system to track the given reference input is designed by a well known regulator design method. The implementation of the proposed servo controller for a BLDC motor are completely carried out using a dSPACE DS1104 digital signal processor (DSP). The simulation and experimental results are shown to verify the effectiveness and the applicability of the proposed controller compared to the conventional PI controller for speed control of the BLDC motor with a step type of disturbance and 3 types of the references such as step, ramp and parabola.

Modified Model Reference Adaptive Controller for a Nonlinear SISO System with External Disturbance and Input Constraint

This paper proposes on a modified model reference adaptive controller for a nonlinear single input-single output system with uncertain modeling, external disturbance, measurement noise and input constraint. The modified model reference adaptive controller not only can be applied for an uncertain modeling system but also can guarantee a good tracking performance in transient and steady-state phases. Applying dead-zone modification can avoid the drift phenomenon of the estimate controller parameters due to the integration procedure in the presence of disturbance external and measurement noise. As well, an auxiliary system is integrated into the control system to compensate the dynamic error caused by the adverse effect of the input constraint. The experimental results on a servomechanism using the proposed controller can be brought out to verify the performance and the effectiveness.

Measurement of the Fish Body Wound Depth Based on a Depth Map Inpainting Method

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.

Locomotion Control of a Hexapod Robot with Tripod Gait Using Central Pattern Generator Network

This paper presents locomotion control of a hexapod robot with tripod gait using central pattern generator (CPG) network. To do this task, the followings are done. First, kinematic modeling of one leg with four links and four rotational joints of hexapod robot is proposed using Denavit-Hartenberg (DH) convention. Second, the walking gait of hexapod robot is generated by central pattern generator network. Third, mapping functions are proposed to map the output of CPG network into a desired trajectory of the end effector of the hexapod robot. It is difficult and complex to get the angles of four rotational joints of one leg using inverse kinematics. To solve this problem, differential kinematics algorithm is used to realize the end effector following the trajectory obtained by the mapping functions for six legs. Finally, simulation results for walking motion of the hexapod robot are shown to prove the effectiveness and applicability of the proposed controller.

Locomotion Control of a Hexapod Robot Based on Central Pattern Generator Network

This paper presents locomotion control of a hexapod robot based on central pattern generator (CPG) network. To do this task, the followings are done. First, kinematic modeling of one leg with four links and four rotational joints of hexapod robot is proposed using Denavit Hartenberg (DH) convention. Second, the walking gait of hexapod robot is generated by central pattern generator network. Third, mapping functions are proposed to map the output of CPG network into a desired trajectory of the end effector of the hexapod robot. It is difficult and complex to get the angles of four rotational joints of one leg using inverse kinematics. To solve this problem, differential kinematics algorithm is used to realize the end effector following the trajectory obtained by the mapping functions. Finally, simulation and experimental results for walking motion of one leg of the hexapod robot are shown to prove the effectiveness and applicability of the proposed controller.

Controller Design for MIMO Servo System Using Polynomial Differential Operator – A Solution for Increasing Speed of an Induction Conveyor System

Improving speed of a belt conveyor system would reduce the cost and reduce downtime. This paper proposes a solution for increasing speed of a belt driven transmission section in an induction conveyor system by applying multi input multi output (MIMO) robust servo controller design method using polynomial differential operator based on the internal model principle. The servo system design is done as follows. Firstly, modeling for a belt driven transmission section in an induction conveyor system is described. Secondly, an extended system including reference and disturbance in polynomial differential equation form is introduced. Based on the extended system, controllability analysis of the extended system is derived. Finally, a state feedback control law for the servo system to track the given reference input is designed by a well known regulator design method. The implementation of the proposed servo controller for a belt driven transmission section is completely carried out using an ARM STM32F103ZE microprocessor. The simulations and experimental results show the effectiveness of the proposed servo controller compared to the conventional PI controller and MRAC controller for high speed control of a belt driven transmission section in an induction conveyor system with a step type of disturbance and 3 types of the references such as step, ramp and trapezoidal, etc.