Ka C. Cheok

Estimation of absolute vehicle speed using fuzzy logic rule-based Kalman filter

Accurate knowledge on the absolute or true speed of a vehicle, if and when available, can be used to enhance advanced vehicle dynamics control systems such as anti-lock brake systems (ABS) and auto-traction systems (ATS) control schemes. Current conventional method uses wheel speed measurements to estimate the speed of the vehicle. As a result, indication of the vehicle speed becomes erroneous and, thus, unreliable when large slips occur between the wheels and terrain. This paper describes a fuzzy rule-based Kalman filtering technique which employs an additional accelerometer to complement the wheel-based speed sensor, and produce an accurate estimation of the true speed of a vehicle. We use the Kalman filters to deal with the noise and uncertainties in the speed and acceleration models, and fuzzy logic to tune the covariances and reset the initialization of the filter according to slip conditions detected and measurement-estimation condition. Experiments were conducted using an actual vehicle to verify the proposed strategy.

Accurate differential global positioning system via fuzzy logic Kalman filter sensor fusion technique

The ability to determine an accurate global position of a vehicle has many useful commercial and military applications. The differential global positioning system (DGPS) is one of the practical navigation tools used for this purpose. However, the DGPS has limitations arising from slow updates, signal interference, and limited accuracy. This paper describes how vehicle rate sensors ran be used to help a DGPS overcome these limitations. The theoretical background for the sensor fusion is based on the principle of Kalman filtering and a fuzzy logic scheme. Validity of the method was verified by using experimental data from an actual automobile navigating around an urban area. The results demonstrated that the path of the automobile can be continuously traced with high accuracy and repeatability, in spite of the limitations of the DGPS.

Exact methods for determining the kinematics of a stewart platform using additional displacement sensors

The Stewart platform (SP) is a parallel closed-kinematic chain robotic mechanism that is capable of providing high structural and positional rigidity. Because of its unique capability, the platforms have been employed in many control engineering applications such as simulator shakers, robotic manipulators, etc. However, a main problem often found in the implementation of a real-time controller for the platform is the lack of an efficient algorithm for solving its highly nonlinear forward kinematic transformation (FKT), where one seeks to find the translational and orientational altitudes of the moveable platform from knowing the lengths of the platform linkages. This article describes two new direct and exact methods for computing the translational and rotational displacements of an SP by employing extra transnational displacement sensors (TDSs), in addition to the existing TDSs for the six links of the SP. The key for the approach lies in knowing where to employ the TDSs for determining positional vectors of strategic platform locations. By taking advantage of a tetrahedral geometry, closed-form solutions for the FKT can then be derived and directly evaluated. The new methods produce accurate solutions with only minimal computation necessary. The advantages and disadvantages of the proposed methods are discussed and compared to an existing method. The exact methods are being investigated for an on-line implementation of a nonlinear adaptive control system and redundancy scheme for a 25-ton Stewart platform-based Crew Station/Turret Motion Base Simulator (CS/TMBS) at the U.S. Army Tank-Automotive Command (TACOM).

A fuzzy logic-based smart automatic windshield wiper

An innovation for a standard intermittent windshield wiper is the concept of a smart wiper that automatically turns itself on or off and adjusts its wiping cycle according to the intensity of rain. This article describes the development of a smart automatic windshield wiper system using a fuzzy logic-based conductive rain sensor scheme. Fuzzy logic is used to compensate nonlinearities in the sensor and implement intuitive reasoning for automatic operation of the wiper. An M68HC11-based microcontroller was developed to implement and test the smart wiper concept for a car. The proposed approach can be extended to other applications related to rain detection and system actuation.

UWB tracking of mobile robots

A local positioning system (LPS) for tracking mobile robots using a newly developed ultra-wideband (UWB) ranging radio technology is presented in this paper. However, measured ranges from these radios often have uncertain biases and large sporadic errors due to multipath and attenuation effect. A fuzzy neighborhood tracking filtering technique was developed to deal with the range outlier problems. A progressive update trilateration filter technique is introduced. The paper then describes a UWB LPS based on triangulation or trilateration of the ranges, which is fused with other vehicle kinematics/dynamics sensors including a compass, rate gyros and wheel speed sensors. The UWB LPS was applied to navigation and guidance of an experimental autonomous mobile robot. Simulation theoretical and real-time experimental results were validated against the true results of the experiment recorded by video.

A fuzzy logic intelligent control system paradigm for an in-line-of-sight leader-following HMMWV

A hierarchical intelligent control system paradigm for a vision-based autonomous driving scheme is presented for a leader-following HMMWV. This article shows how fuzzy logic is employed to represent knowledge at the organization level, how to resolve conflicting perceived information at the coordination level, and how to carry out the best action for the vehicle at the execution level. After introducing the methodology, simulation and experimental aspects for realizing and testing the scheme are discussed. ©1997 by John Wiley & Sons, Inc.

Fuzzy Logic Rule-Based Kalman Filter for Estimating True Speed of A Ground Vehicle

ABSTRACTAccurate knowledge on the true ground speed of a vehicle, if available, can be used to enhance advanced vehicle dynamics control systems such as anti-lock brake systems (ABS) and traction control systems (TCS) control schemes. This article describes a fuzzy rule-based Kalman filtering technique that employs an additional accelerometer to complement the wheel-based speed sensor, and produce a more accurate estimation of the true speed of a vehicle. Application of the fuzzy logic rule-based Kalman filter shows that better estimates of the true speed can be achieved even under significant braking skid and traction slip conditions.

Comparison of optimal path planning algorithms for an autonomous mobile robot

In this paper, an optimal control approach is used to solve a two-dimensional path planning problem for a differential drive mobile robot. Two optimal control algorithms are presented and analyzed, which consist of a novel implementation of a linear quadratic tracker (LQT), and a dynamic programming (DP) scheme. The algorithms are applied to the task of GPS navigation with obstacle avoidance. The methods aim to find an optimal path where the tracking error to the GPS target is minimized, while avoiding the obstacles present on the vehicles map. The LQT algorithm minimizes the tracking error to the goal point, while simultaneously maximizing the distance to obstacles. It also makes use of a fuzzy logic system to adjust the optimization parameters according to different environmental scenarios.

Accurate global positioning via fuzzy logic Kalman filter-based sensor fusion technique

The ability to determine accurate global position of a vehicle has many useful commercial and military applications. Differential Global Positioning System (DGPS) is one of the practical navigation tools used for this purpose. However, DGPS has limitations arising from slow updates, signal interference and limited accuracy. This paper describes how vehicle rate sensors can be used to help a DGPS overcome these limitations. The theoretical background for the sensor fusion is based on the principle of Kalman filtering and a fuzzy logic scheme. Validity of the method was examined by using experimental data from an actual automobile navigating around an urban area. The results demonstrated that the path of the automobile can be continuously traced with high accuracy and repeatability.

Experimental Implementation of Lyapunov based MRAC for Small Biped Robot Mimicking Human Gait

The chapter presents an approach to control the biped humanoid robot to ambulate through human imitation. For this purpose a human body motion capturing system is developed using tri-axis accelerometers (attached to human legs and torso). The tilt angle patterns information from the human is transformed to control and teach various ambulatory skills for humanoid robot bipedalism. Lyapunov stability based model reference adaptive controller (MRAC) technique is implemented to address unpredictable variations of the biped system.