R.M.H. Cheng

A new control strategy for tracking in mobile robots and AGVs

The tracking problem of a wheeled mobile robot or an automated guided vehicle is considered. For the vehicles with a steering wheel, a control strategy is proposed to determine the steering angle at each instant based on measured errors, i.e. the offset from the path and the deviation in orientation. The results of computer simulation of the dynamics of the system and comparisons with other proposed control policies are presented. It is shown that by implementing the new policy significant improvement in tracking capability can be achieved.<<ETX>>

Neuromorphic controller for AGV steering

A backpropagation neural network is proposed as a controller for an automated guided vehicle (AGV) system. At the present stage of development, the input layer consists of two neurons and receives the state signals of the tracking errors from the camera image processor, and the sole neuron in the output layer provides the command signal of a reference yaw rate signal for the vehicle. Simulations and preliminary experimentation on a prototype vehicle showed that one hidden layer was adequate to provide good driving for such a time-varying nonlinear dynamic system. A comparison with a previous proportional controller is included.<<ETX>>

Analysis of steering control in vehicles with two independent left and right traction wheels

Based on the kinematic studies of motion for a vehicle equipped with a pair of motorized wheels which, by having appropriate velocities, can provide traction forces as well as steering action, a steering control strategy is derived. The angular velocities for the right and left wheels are considered, the two control inputs which cause a system to follow a desired trajectory. Assuming these inputs to be linear functions of the two errors associated with path tracking problem (position and orientation errors), through an appropriate Lyapunov function, a control policy is determined. The path tracking behaviour of a mobile robot using such a control law is demonstrated by computer simulation.<<ETX>>

Control of a wheeled mobile robot with double steering

The motion of a vehicle with automated guidance (an AGV or a wheeled mobile robot) equipped with two steerable traction wheels in the front and rear is studied. Compared with a conventional form of these vehicles, there is some degree of redundancy in their system of path tracking. If this redundancy is utilized appropriately, there are certain advantages over the conventional vehicles in terms of their performance in path tracking. A scheme for steering control of this class of vehicle is proposed. Simulation results demonstrate the good performance of a vehicle controlled according to the proposed scheme.<<ETX>>

A guidance control scheme for accurate track following of AGVs

The authors present a guidance scheme that provides accurate tracking and faster minimization of tracking errors of the front and rear ends of automatic guided vehicles (AGVs). Sensors provided at the front and rear provide the position and orientation of the front and rear ends of the vehicle relative to the track. Control laws that make use of this information have been devised to speedily achieve accurate tracking of the front and rear ends of the vehicle with minimum overshoots. The control laws are chosen based on the presence or absence of curvature and also based on the relative location of the longitudinal axis of the vehicle relative to the track. The gains are modified online to achieve proper tracking. Simulation results are provided for illustration.<<ETX>>

Dynamic modelling and control of wheeled mobile robots theory and experiment

Very little experimental investigation has been reported in the recent research in dynamic modelling and control of wheeled mobile robots (WMR). To address the issue of experimentation several prototype vehicles (CONCIC I to III) have been built to supplement the research program at the Centre for Industrial Control of Concordia University in this area. The paper concentrates on the latest development of CONCIC III. A control strategy is proposed for path tracking and its implementation. Some initial but promising results obtained from the dynamic model and experimental data are presented, showing the accuracy of the dynamic model as well as the effectiveness of the control algorithm.<<ETX>>

A predictor-corrector guidance control scheme for AGV navigation

This paper presents a scheme that employs feedforward control in conjunction with a predictor-corrector scheme for guidance control of Automated Guided Vehicles (AGVs). The predictor-corrector scheme provides the desired values of steering parameters which depend on the geometry of the track and a driving criterion. The geometry of the track/road ahead of the vehicle is obtained by extrapolating the identified (estimated) geometry of the track/road traversed during the elapsed time interval. This real-time identification is carried out by fitting a curve to the path traversed by the vehicle. The coordinates of the path are provided by a transformation formulation which makes use of the motion parameters and a kinematic model of the vehicle. The driving criterion specifies the positioning of the AGV on the track. Several possible criteria are identified in the paper and mathematical formulations are presented for one such criterion. Results of off-line calculations using simulated track profiles and experimental data obtained using a prototype AGV while following various track profiles are provided for illustration.

Parametric study and sensitivity analysis of automated vehicles

This paper presents a parametric study of automated vehicles using the sensitivity theory. A sixth order dynamic model of an axisymmetric vehicle is developed in the state space format to represent its 3 degrees-of-freedom motion in the lateral, yaw and roll modes. Variations of the important parameters of the vehicle are grouped into three separate vectors: with the elements consisting of inertia, stiffness and damping, and geometric-kinematic parameters respectively. The effect of every element of these vectors on the state variables is studied carefully, a comparison being made among the state variables to reveal the relative influence of the parameter-induced variations. This helps better understanding which mode of the system is more affected by changes in particular parameters and the severity in the transient response and in the steady-state response. Then the effects of a particular vector on the performance of the system is studied. This provides a global view over the severity of the changes and generates a qualitative understanding as to how overall parameter changes influence the motion of the vehicle.

Design of a Controller with Feedforward Action for Path Tracking of Automated Vehicles

Abstract This paper presents the design of an optimal controller with feedforward action for the path tracking of automated guided vehicles. A linear model is developed to represent a vehicle with front and rear steering. This model is employed in steering controller design of the vehicle. The controller is implemented on a prototype vehicle (CONCIC III). The performance of the controlled system is validated with experimental results.

Linear and Nonlinear Models of Automated Vehicles Analysis and Experiments

Abstract This paper presents some analytical and experimental results regarding dynamic modelling and control of automated wheeled vehicles. Linear and nonlinear models are developed to represent the plane motion of this class of vehicle. An optimal controller is implemented for the tracking of a prototype vehicle CONCIC III. Results regarding the accuracy of the models, verification of the assumptions are reported.