Showing papers by "Ching-Chih Tsai published in 2011"

Parallel Elite Genetic Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation

Abstract: This paper presents a parallel elite genetic algorithm (PEGA) and its application to global path planning for autonomous mobile robots navigating in structured environments. This PEGA, consisting of two parallel EGAs along with a migration operator, takes advantages of maintaining better population diversity, inhibiting premature convergence, and keeping parallelism in comparison with conventional GAs. This initial feasible path generated from the PEGA planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Both global path planner and smoother are implemented in one field-programmable gate array chip utilizing the system-on-a-programmable-chip technology and the pipelined hardware implementation scheme, thus significantly expediting computation speed. Simulations and experimental results are conducted to show the merit of the proposed PEGA path planner and smoother for global path planning of autonomous mobile robots.

FPGA-Based Parallel DNA Algorithm for Optimal Configurations of an Omnidirectional Mobile Service Robot Performing Fire Extinguishment

Abstract: This paper presents a coarse-grain parallel deoxyribonucleic acid (PDNA) algorithm for optimal configurations of an omnidirectional mobile robot with a five-link robotic arm. This efficient coarse-grain PDNA is proposed to search for the global optimum of the redundant inverse kinematics problem with minimal movement, thereby showing better population diversity and avoiding premature convergence. Moreover, the pipelined hardware implementation, hardware/software co-design, and System-on-a-Programmable-Chip (SoPC) technology on a field-programmable gate array (FPGA) chip are employed to realize the proposed PDNA in order to significantly shorten its processing time. Simulations and experimental results are conducted to illustrate the merit and superiority of the proposed FPGA-based PDNA algorithm in comparison with conventional genetic algorithms (GAs) for omnidirectional mobile robot performing fire extinguishment.

Adaptive Robust Self-Balancing and Steering of a Two-Wheeled Human Transportation Vehicle

Abstract: This paper presents adaptive robust regulation methods for self-balancing and yaw motion of a two-wheeled human transportation vehicle (HTV) with varying payload and system uncertainties. The proposed regulators are aimed at providing consistent driving performance for the HTV with system uncertainties and parameter variations caused by different drivers. By decomposing the overall system into the yaw motion subsystems and the wheeled inverted pendulum, two proposed adaptive robust regulators are synthesized to achieve self-balancing and yaw motion control. Numerical simulations and experimental results on different terrains show that the proposed adaptive robust controllers are capable of achieving satisfactory control actions to steer the vehicle.

Global path planning for autonomous robot navigation using hybrid metaheuristic GA-PSO algorithm

Abstract: This paper presents a hybrid metaheuristic GA (genetic algorithm)-PSO (particle swarm optimization) algorithm for autonomous robot navigation to find an optimal path between a starting and ending point in a grid environment. GA has been combined with PSO in evolving new solutions by applying crossover and mutation operators on solutions constructed by particles. This hybrid algorithm avoids the premature convergence and time complexity in conventional GA and PSO algorithms. The initial feasible path generated from the hybrid GA-PSO planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Simulation results are conducted to show the merit of the proposed hybrid GA-PSO path planner and smoother for global path planning of autonomous robot navigation.

Motion controller design and embedded realization for Mecanum wheeled omnidirectional robots

Abstract: This paper presents techniques for design and embedded implementation of a kinematics controller for a Mecanum wheeled omnidirectional robot (MWOR). The kinematic controller is designed based on feedback linearization method, and then shown asymptotically stable via the Lyapunov stability theory. The proposed motion control law has been implemented into an FPGA development board using System-on-a-programmable-chip (SoPC). Simulations and experimental results are conducted to illustrate the effectiveness and performance of the proposed controller for Mecanum wheeled omnidirectional robots.

Adaptive Polar-Space Motion Control for Embedded Omnidirectional Mobile Robots with Parameter Variations and Uncertainties

Abstract: This paper presents an adaptive polar-space motion controller for trajectory tracking and stabilization of a three-wheeled, embedded omnidirectional mobile robot with parameter variations and uncertainties caused by friction, slip and payloads. With the derived dynamic model in polar coordinates, an adaptive motion controller is synthesized via the adaptive backstepping approach. This proposed polar-space robust adaptive motion controller was implemented into an embedded processor using a field-programmable gate array (FPGA) chip. Furthermore, the embedded adaptive motion controller works with a reusable user IP (Intellectual Property) core library and an embedded real-time operating system (RTOS) in the same chip to steer the mobile robot to track the desired trajectory by using hardware/software co-design technique and SoPC (system-on-a-programmable-chip) technology. Simulation results are conducted to show the merit of the proposed polar-space control method in comparison with a conventional proportional-integral (PI) feedback controller and a non-adaptive polar-space kinematic controller. Finally, the effectiveness and performance of the proposed embedded adaptive motion controller are exemplified by conducting several experiments on steering an embedded omnidirectional mobile robot.

Design and experimental evaluation of robust PID and PI-PD temperature controllers for oil-cooling machines

Abstract: This paper presents techniques and methodologies for design and experimental evaluation of both robust PID and PI-PD temperature controllers for oil cooling machine systems. The process of oil cooling machine can be experimentally described as a second-order model with time delay. A robust PID controller with sensitivity specifications is proposed to achieve set point tracking, disturbance rejection, and robustness against time-dependent parameter variations. With the obtained three-term parameters of the robust PID controller, a PI-PD controller is constructed in order to control more general industrial processes or plants. Computer simulations are performed to illustrate the superior performance and merit of the proposed PID and PI-PD controllers in comparison with conventional ones. The applicability and usefulness of the proposed control scheme are well exemplified by conducting experiments on a physical high-speed oil cooling machine. Both simulations and experimental results reveal that the proposed PID and PI-PD scheme outperforms the conventional PID and PI-PD controllers.

Aggregated hierarchical sliding-mode control for spherical inverted pendulum

Abstract: This paper develops methodologies and techniques for modeling and aggregated hierarchical sliding-mode control of a spherical inverted pendulum control system. Lagrangian mechanics is adopted to establish a mathematical model of the system and this model is shown to be consistent with the well-known decoupled model under two special cases. Aggregated hierarchical siding-mode control and backstepping are used to propose a coupled controller so as to maintain the nutation angle at zero and achieve trajectory tracking at the same time. Via Matlab/Simulink, the effectiveness and merit of the proposed controller are exemplified by conducting several simulations on the spherical inverted pendulum system.

Intelligent adaptive trajectory tracking control using fuzzy basis function networks for an autonomous small-scale helicopter

Abstract: This paper presents an intelligent adaptive trajectory tracking controller using fuzzy basis function networks (FBFN) for an autonomous small-scale helicopter. With the on-line FBFN approximation to the vehicle mass and the coupling effect between the force and the moments, the intelligent adaptive controller is systematically synthesized using backstepping technique. This controller is shown to achieve the semi-global ultimate boundedness of the closed-loop helicopter dynamics and accommodate agile flight maneuvers in trajectory tracking. The effectiveness and merit of the proposed method are exemplified by performing one nonlinear simulation and by performance comparison with a well-known controller.

Face detection, identification and tracking using support vector machine and fuzzy Kalman filter

Abstract: This paper presents methodologies and techniques for human face detection, identification and tracking used for a human-robot interactive system. A fuzzy skin color adjuster together with standard image processing algorithm is proposed to detect human faces, and then identify them using the nonlinear support vector machine (SVM) and the Euclidean distance measure. A fuzzy Kalman filtering scheme is presented to track the identified human faces. Experimental results are conducted to verify the effectiveness and merit of the three proposed methods.

Autonomous task execution using stereo vision camera for a two-armed service robot

Abstract: This paper presents techniques and methodologies for how to use two cooperating arms along with the stereo vision system to execute a complicated task automatically for a two-armed service robot. Via standard image processing, the stereo vision system recognizes objects in the task and then obtain their positions with respect to the stereo vision camera. The positions are transformed into those with respect to the reference frame of the dual arms. With those known objects, a general procedure for autonomous task execution is presented, and then an interesting coffee making task is used to illustrate the procedure done by the robot. Several experiments are conducted to illustrate the effectiveness and merit of the proposed autonomous task execution procedure for a two-armed service robot.

Intelligent adaptive trajectory tracking using fuzzy basis function networks for self-balancing two-wheeled mobile robots

Abstract: This paper presents an intelligent adaptive backstepping sliding-mode motion controller using fuzzy basis function networks (FBFN) method for trajectory tracking of a self-balancing two-wheeled robot (SBTWR) with parameter variations. A decoupling method is proposed to decouple the robot's dynamic model such that the tracking controller can be synthesized using backstepping and sliding-mode control in both kinematic and dynamic levels. The FBFN is employed to on-line learn the uncertain parts of the tracking controller, thus achieving adaptive capability. Simulations results indicate that the proposed adaptive tracking controller is capable of providing satisfactory trajectory tracking performance.

3D Collision-Free Trajectory Generation Using Elastic Band Technique for an Autonomous Helicopter

Abstract: A real-time path generation based on the elastic band technique is presented to find a collision-free trajectory for an autonomous small-scale helicopter flying through cluttered, dynamic three-dimensional (3D) environments. The dynamic path is followed by the adaptive trajectory tracking controller augmented with the radial basis function neural networks (RBFNN). The effectiveness and merit of the proposed method are exemplified by performing three simulation scenarios: static obstacle avoidance, dynamic obstacle avoidance and terrain following.

Adaptive dynamic motion control using ant colony optimization for nonholonomic mobile robots

Abstract: This paper presents techniques to design a dynamic motion controller using Ant Colony Optimization (ACO) for simultaneous stabilization and tracking of nonholonomic mobile robots. A unified dynamic motion controller is first designed based on the Lyapunov stability theory and adaptive backstepping technique, and ACO is then applied to search for the best control parameters of the proposed dynamic controller. Simulations are conducted to illustrate the performance of the proposed controller.