Hsu-Chih Huang

Adaptive Neural Network Control of a Self-Balancing Two-Wheeled Scooter

This paper presents an adaptive control using radial-basis-function neural networks (RBFNNs) for a two-wheeled self-balancing scooter. A mechatronic system structure of the scooter driven by two dc motors is briefly described, and its mathematical modeling incorporating two frictions between the wheels and the motion surface is derived. By decomposing the overall system into two subsystems (yaw motion and mobile inverted pendulum), one proposes two adaptive controllers using RBFNN to achieve self-balancing and yaw control. The performance and merit of the proposed adaptive controllers are exemplified by conducting several simulations and experiments on a two-wheeled self-balancing scooter.

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

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 Implementation of an Embedded Robust Adaptive Controller for Autonomous Omnidirectional Mobile Platform

This paper presents an embedded adaptive robust controller for trajectory tracking and stabilization of an omnidirectional mobile platform with parameter variations and uncertainties caused by friction and slip. Based on a dynamic model of the platform, the adaptive controller to achieve point stabilization, trajectory tracking, and path following is synthesized via the adaptive backstepping approach. This robust adaptive controller is then implemented into a high-performance field-programmable gate array chip using hardware/software codesign technique and system-on-a-programmable-chip design concept with a reusable user intellectual property core library. Furthermore, a soft-core processor and a real-time operating system are embedded into the same chip for realizing the control law to steer the mobile platform. Simulation results are conducted to show the effectiveness and merit of the proposed control method in comparison with a conventional proportional-integral feedback controller. The performance and applicability of the proposed embedded adaptive controller are exemplified by conducting several experiments on an autonomous omnidirectional mobile robot.

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

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

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.

Simultaneous tracking and stabilization of an omnidirectional mobile robot in polar coordinates: A unified control approach

This paper presents a polar-space kinematics control method to achieve simultaneous tracking and stabilization for an omnidirectional wheeled mobile robot with three independent driving omnidirectional wheels equally spaced at 120° from one another. The kinematic model of the robot in polar coordinates is presented. With the kinematic model, a kinematic control method based on feedback linearization is proposed in order to achieve simultaneous tracking and stabilization. The proposed method is easily extended to address the path following problem. Computer simulations and experimental results are presented to show the effectiveness and usefulness of the proposed control method at slow speeds.

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

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.

Adaptive Trajectory Tracking and Stabilization for Omnidirectional Mobile Robot with Dynamic Effect and Uncertainties

Abstract This paper presents an adaptive backstepping control method for trajectory tracking and stabilization of an omnidirectional wheeled mobile robot with parameter variations and uncertainties caused by friction and slip. The dynamic model of the robot with three independent driving omnidirectional wheels equally spaced at 120 degrees from one another is briefly introduced. With the dynamic model, the adaptive controller to achieve both trajectory tracking and stabilization is synthesized via adaptive backstepping approach. Experimental results are conducted to show the merit of the proposed control method.

Simultaneous tracking and stabilization of an omnidirectional mobile robot in polar coordinates

Abstract This paper presents polar‐space kinematic and dynamic control methods to achieve both trajectory tracking and stabilization for an omnidirectional wheeled mobile robot with three independent, omnidirectional, driving wheels equally spaced at 120 degrees from one another. Both kinematic and dynamic models of the robot in polar coordinates are presented. A kinematic control method is proposed based on feedback linearization and the kinematic model, whereas a dynamic controller is synthesized using backstepping and the dynamic model. Experimental results are presented to show the efficacy and usefulness of the proposed control methods.

Autonomous navigation of an indoor tour guide robot

This paper develops methodologies and techniques for autonomous navigation of a tour-guide robot with a human-robot interaction system. The designed navigation system includes global localization, dynamic path planning, local goal-seeking, safe obstacle-avoidance, behavior fusion, and autonomous robot control. The RFID module for global pose initialization is presented based on the RSSI measurements, the proposed calibration method and least square method. With the gross initial robot pose, accurate robot pose tracking are achieved by fusing the RFID data and laser scanning measurements utilizing an extended Kalman filter. The global path is generated by dynamic programming method. The Petri-net model is employed to construct the event-driven logic control sequence from the present states of the robot and assigned tour missions. An operational scenario is used to show the effectiveness of the proposed autonomous navigation method.