Automatic Path Tracking Research Articles

Gain-Scheduled Steering and Braking Coordinated Control in Path Tracking of Intelligent Heavy Vehicles

Abstract In the context of intelligent transportation system and advanced vehicle control system, higher requirements for intelligent control and coordinated control of heavy vehicles (HVs) have been proposed. Automatic path tracking control is essential for automatic driving of heavy vehicles. However, uncertain lateral disturbances and time-varying characteristics of system parameters make it difficult to guarantee roll stability and path tracking accuracy during automatic path tracking. This paper investigates the coordination of active front steering (AFS) and direct yaw moment control (DYC) in the automatic path tracking system for intelligent heavy vehicles. The main idea is to adjust the braking action according to the rollover risk evaluated by a specific rollover index (RI). The coordination of steering and braking systems and the robustness of the system against time-varying parameters are achieved by a gain-scheduled linear parameter varying (LPV) controller. Based on the linear matrix inequality (LMI) framework, the LPV controller is synthesized to ensure the robust H∞ performance against external disturbances. Simulation results show that the proposed gain-scheduled LPV/H∞ control strategy can enhance roll stability and path tracking accuracy in the path tracking process of intelligent heavy vehicles.

Motion characteristics of untethered swimmer with magnetoelastic material

Cable-less micro-robots have exhibited promising potential for conducting tasks in small and constrained environments through remote controlling approaches. Soft robots formed by magnetic composites have drawn rising attention, and have demonstrated their capability to be wirelessly controlled in both dry and wet working environments. This paper presents a swimmer propelled by its undulatory deformation using a magnetoelastic composite material. The swimmer can move freely on water surface driven through magnetic field generated by 3D Helmholtz coils, allowing forward and backward motion as well as steering with different velocity ranging from 0 to 14.9 mm s−1. To further study the characteristics of the swimmer, the force and torque equilibrium equations were established, and deformation of swimmer in response to different magnetic field was analyzed and described. The relationship between the parameters of magnetic field and the properties of the swimmer was obtained through analytical calculation, finite element modeling (FEM) and experiments. Furthermore, a closed-loop controlled system was developed to allow automatic path tracking and PID control of the swimmer, leading to distance errors and steering errors within ±0.36 mm and ±18.2° respectively. The swimmer and its mathematical model have suggested effective control through changing the parameters of external magnetic field. The swimmer may serve as soft surgical robots and drug delivers for biomedical and healthcare applications.

Autonomous Mobile Ground Control Point Improves Accuracy of Agricultural Remote Sensing through Collaboration with UAV

Ground control points (GCPs) are critical for agricultural remote sensing that require georeferencing and calibration of images collected from an unmanned aerial vehicles (UAV) at different times. However, the conventional stationary GCPs are time-consuming and labor-intensive to measure, distribute, and collect their information in a large field setup. An autonomous mobile GCP and a collaboration strategy to communicate with the UAV were developed to improve the efficiency and accuracy of the UAV-based data collection process. Prior to actual field testing, preliminary tests were conducted using the system to show the capability of automatic path tracking by reducing the root mean square error (RMSE) for lateral deviation from 34.3 cm to 15.6 cm based on the proposed look-ahead tracking method. The tests also indicated the feasibility of moving reflectance reference panels successively along all the waypoints without having detrimental effects on pixel values in the mosaicked images, with the percentage errors in digital number values ranging from −1.1% to 0.1%. In the actual field testing, the autonomous mobile GCP was able to successfully cooperate with the UAV in real-time without any interruption, showing superior performances for georeferencing, radiometric calibration, height calibration, and temperature calibration, compared to the conventional calibration method that has stationary GCPs.

An Improved Fuzzy Logic Control Method for Path Tracking of an Autonomous Vehicle

Highlights This study focused on the path tracking accuracy of a two-wheel steering, two-wheel drive autonomous vehicle. An improved fuzzy logic control method (IFM) was designed to control the steering angle of the front wheels. The IFM was better than traditional pure pursuit and fuzzy logic control methods for automatic path tracking. Abstract. This article presents a path-tracking algorithm based on an improved fuzzy logic control method (IFM) that generates optimal steering angles for an autonomous wheeled vehicle to track a sequence of waypoints. The path-tracking algorithm was designed to focus on the vehicle performance, including tracking accuracy, stability, and convergence speed. A prototype vehicle with two-wheel steering and two-wheel drive (2WS-2WD) was developed as a test platform and equipped with a series of sensors for evaluating the IFM. In this study, we considered two variables, i.e., lateral deviation (d) and heading deviation (θ), as inputs for the control system. The output (δ) was the steering angle of the front wheels as controlled by an electric linear actuator. A maximum steering angle strategy was adopted for rapid convergence when the vehicle was far from the desired path or when the heading deviation was large. An update-line distance algorithm was used for finding the best turning time as the vehicle moved closer to the next waypoint. To validate the proposed algorithm, testing was performed to compare traditional pure pursuit (TPP), traditional fuzzy logic control method (TFM), and the IFM in tracking two types of paths (straight and rectangular). Traveling at 0.5 m s-1 and with a signal sampling period of 0.5 s, the prototype converged to the desired straight path from different initial states. When the vehicle reached a stable state, the steady-state error was between 5.0 and 6.5 cm with a mean of ≤6.0 cm. The settling distance in the straight path test was between 125.0 and 422.3 cm, and the convergence time was in the range of 11.5 to 16.0 s; the greater the initial deviation of the vehicle was, the greater the settling distance and settling time were. In the 15 m x 14 m rectangular path test, the overall mean error of the IFM was 14.4 cm when the initial lateral and heading deviations were 0, and the maximum deviation was 67.4 cm, which occurred at the corners. The test results show that the proposed IFM had better accuracy, stability, and convergence speed for path tracking when compared to the TPP and TFM algorithms.

Tractor path tracking control based on binocular vision

In the process of field operation management, determining how to accurately realize crop row identification and path tracking control is an essential part of tractor automatic navigation. According to the linear operation in the process of cotton field management, the tractor path tracking control system was designed based on binocular vision and the pure pursuit model. A new crop row detection method based on the Census transform and the PID control algorithm with dead zone were used. First, the upper computer software was developed by C++ with the functions of parameter setting and image acquisition and processing. Second, an automatic steering controller was developed based on microprocessor MC9S12XS128 of Freescale. The control program was developed based on modular design using CodeWarrior during development of the PID-based automatic steering control strategy. Finally, a field experiment platform of tractor path tracking control was built, and field experiments under the actual cotton were conducted. The optimal visibility distance was determined by several previous experiments. When the tractor tracks the path with the optimal visibility distance in the growth environment of actual cotton crops, the mean absolute deviation of course angle was 0.95°, and the standard deviation was 1.26°; the mean absolute deviation of lateral position was 4.00 cm, and the standard deviation was 4.97 cm; the mean absolute deviation of front wheel angle was 2.99°, and the standard deviation was 3.67°. The experimental results show that (1) the crop row detection method based on Census transform can identify the crop line and plan the navigation path well, and (2) the tractor path tracking control system based on binocular vision has good stability and high control precision; thus, the control system can realize the automatic path tracking control of cotton line operation and meets the agricultural requirements of cotton field operation management.

Automatic Path Tracking and Target Manipulation of a Magnetic Microrobot.

Recently, wireless controlled microrobots have been studied because of their great development prospects in the biomedical field. Electromagnetic microrobots have the advantages of control agility and good precision, and thus, have received much attention. Most of the control methods for controlling a magnetic microrobot use manual operation. Compared to the manual method, the automatic method will increase the accuracy and stability of locomotion and manipulation of microrobots. In this paper, we propose an electromagnetic manipulation system for automatically controlling the locomotion and manipulation of microrobots. The microrobot can be automatically controlled to track various paths by using visual feedback with an expert control algorithm. A positioning accuracy test determined that the position error ranges from 92 to 293 μm, which is less than the body size (600 μm) of the microrobot. The velocity of the microrobot is nearly proportional to the applied current in the coils, and can reach 5 mm/s. As a micromanipulation tool, the microrobot is used to manipulate microspheres and microgears with the automatic control method. The results verify that the microrobot can drag, place, and drive the microstructures automatically with high precision. The microrobot is expected to be a delicate micromachine that could play its role in microfluidics and blood vessels, where conventional instruments are hard to reach.

Design of Automatic Aquaculture Workboat Driven by Air Propellers

At present, artificial bait casting and water quality detection are widely used in the domestic aquaculture, it is difficult to improve the yield and quality of the output of aquatic products such as fish, prawn and crab because of low production efficiency and limited labor force. This paper proposed an automatic aquaculture workboat driven by air propellers based on 3G(GNSS、GIS、GPRS), equipped with main controller ARM11, automatic path planning and tracking based on GIS and GNSS system and remote monitoring with GPRS communication module, the workboat can perform bait casting and water quality parameters detection such as dissolved oxygen, pH, water temperature, ammonia nitrogen and salinity automatically according to the aquaculture tasks. It can improve the aquaculture work efficiency and save the manpower and the material resources.

Coupled nonlinear vehicle control: Flatness-based setting with algebraic estimation techniques

A combined nonlinear longitudinal and lateral vehicle control is investigated. Flatness-based nonlinear control and new algebraic estimation techniques for noise removal and numerical differentiation are the main theoretical tools. An accurate automatic path-tracking via vehicle steering angle and driving/braking wheel torque is thus ensured. It combines the control of the lateral and longitudinal motions in order to track straight or curved trajectories and to perform a combined lane-keeping and steering control during critical driving situations such as obstacle avoidance, stop-and-go control, lane-change maneuvers or any other maneuvers. Promising results have been obtained with noisy experimental data, which were acquired by a laboratory vehicle with high dynamic loads and high lateral accelerations.

Nonlinear sliding mode control of an unmanned agricultural tractor in the presence of sliding and control saturation

The paper considers the problem of automatic path tracking by autonomous farming vehicles subject to wheel slips, which are characteristic for agricultural applications. Two guidance laws are proposed to solve this problem, and both explicitly take into account the constraints on the steering angle and ensure tracking an arbitrarily curved path. The first law is implemented by the pure sliding-mode controller, whereas the second one combines the sliding mode approach with a smooth nonlinear control law and requests control chattering at the reduced amplitude as compared with the first law. Mathematically rigorous proofs of global convergence and robust stability of the proposed guidance laws are presented. In doing so, the slipping effects are treated as bounded uncertainties. Simulation results and real world experiments confirm the applicability and performance of the proposed guidance approach.

Double look-ahead reference point control for autonomous agricultural vehicles

A simple automatic path tracking system is developed to satisfy the typical requirements of an unmanned agricultural tractor application based on two look-ahead reference points (2-LARP) on the desired path. The main objective of the proposed control system is to track a desired path within reasonable tolerances of a typical farming process including considerable slippage. The employed look-ahead reference points provide compensation for the centrifugal forces and reduction of the peak lateral deviation due to curvature transition, using only simple arithmetic operations. Extensive numerical tests were carried out on the computer simulation of the system dynamics driven by the proposed control method. Simulation results indicate enhancements in vehicle manoeuvrability. Tests indicated that the peak lateral displacement error at the curvature transitions is reduced to one fifth of single LARP error. ► Simple path tracking for agricultural vehicles using 2 look-ahead reference points. ► Lateral deviations similar to an exponentially decaying 6th order dynamic system. ► One look-ahead reference compensates for centrifugal forces over large speed range. ► Second look-ahead reference reduces the peak deviation at curvature transitions. ► The proposed controller reduces the peak error at curvature transitions.

수중항법 알고리즘을 위한 미내로 운동학 파라미터 예측

A test miner named MineRo was constructed for the purpose of shallow water test of mining performance. In June of 2009, the performance test was conducted in depth of 100 m, 5 km away from Hupo-port (Korean East Sea), to assess if the developed system is able to collect and lift manganese nodules from seafloor. In August of 2010, in-situ test of automatic path tracking control of MineRo was performed in depth of 120 m at the same site. For path tracking control, a localization algorithm determining MineRo's position on seabed is prerequisite. This study proposes an improved underwater navigation algorithm through estimation of MineRo's kinematic parameters. In general, the kinematic parameters such as track slips and slip angle are indirectly calculated using the position data from USBL (Ultra-Short Base Line) system and heading data from gyro sensors. However, the obtained data values are likely to be different from the real values, primarily due to the random noise of position data. The aim of this study is to enhance the reliability of the algorithm by measuring kinematic parameters, track slips and slip angle.

Automatic path-tracking controller of a four-wheel steering vehicle

The present paper proposes an automatic path-tracking controller of a four-wheel steering (4WS) vehicle based on the sliding mode control theory. The controller has an advantage in that the front- and rear-wheel steering can be decoupled at the front and rear control points, which are defined as centres of percussion with respect to the rear and front wheels, respectively. Numerical simulations using a 27-degree-of-freedom vehicle model demonstrated the following characteristics: (1) the automatic 4WS controller has a more stable and more precise path-tracking capability than the 2WS controller, and (2) the automatic 4WS controller has robust stability against system uncertainties such as cornering power perturbation, path radius fluctuation, and cross-wind disturbance.

An approach of constraining wheel slip for automatic path tracking control of 4WS/4WD vehicles

Constraining wheel slip can be applied to avoid vehicle skidding, especially on a slippery road. This paper presents an approach of constraining wheel slip for automatic path tracking control of 4WS/4WD vehicles. The approach integrates and limits the quasi-steady state of both the longitudinal and lateral wheel slips. A new control structure of wheel torque and wheel steering is proposed to transform the original constraint-tracking problem to that of state regulation with input constraint. For the transformed problem, a low-and-high gain technique and an integral compensator are introduced to construct the constrained controller, so that the utilization of the constrained wheel slip can be enhanced and the steady state error of tracking can be eliminated. Simulation shows that, on the snow road condition, the proposed scheme can render the 4WS/4WD vehicle tracking along the desired path within a prescribed threshold of wheel slip, and can provide satisfactory coordination between wheel torque and wheel steering

Fast extraction of minimal paths in 3D images and applications to virtual endoscopy

The aim of this article is to build trajectories for virtual endoscopy inside 3D medical images, using the most automatic way. Usually the construction of this trajectory is left to the clinician who must define some points on the path manually using three orthogonal views. But for a complex structure such as the colon, those views give little information on the shape of the object of interest. The path construction in 3D images becomes a very tedious task and precise a priori knowledge of the structure is needed to determine a suitable trajectory. We propose a more automatic path tracking method to overcome those drawbacks: we are able to build a path, given only one or two end points and the 3D image as inputs. This work is based on previous work by Cohen and Kimmel [Int. J. Comp. Vis. 24 (1) (1997) 57] for extracting paths in 2D images using Fast Marching algorithm.Our original contribution is twofold. On the first hand, we present a general technical contribution which extends minimal paths to 3D images and gives new improvements of the approach that are relevant in 2D as well as in 3D to extract linear structures in images. It includes techniques to make the path extraction scheme faster and easier, by reducing the user interaction.We also develop a new method to extract a centered path in tubular structures. Synthetic and real medical images are used to illustrate each contribution.On the other hand, we show that our method can be efficiently applied to the problem of finding a centered path in tubular anatomical structures with minimum interactivity, and that this path can be used for virtual endoscopy. Results are shown in various anatomical regions (colon, brain vessels, arteries) with different 3D imaging protocols (CT, MR).

Investigation of automatic path tracking using an extended Kalman filter

This paper proposes a lane marker recognition method that uses the steering angle in addition to image information. A Kalman filter was reconfigured regarding the yaw motion and lateral motion of lane markers, previously treated as a stochastic process, as the states of a vehicle model driven on the basis of the steering angle. Driving tests conducted with an actual vehicle verified that this method provides good tracking at the time of steering input and avoids misrecognition of lane marker candidate points in inclement weather.

Efficacy of automatic path tracking in virtual colonoscopy

Virtual colonoscopy is a minimally invasive technique allowing early detection of colorectal polyps. Several visualization techniques exist to inspect this large amount of data on the presence of lesions. The most common ones are slice-by-slice viewing, multiplanar reformatting and perspective volume rendering of the inner colon wall (virtual endoscopy). A path or centerline through the colon can be very useful to perform virtual endoscopy. Frequently, this path has to be tracked manually. Unfortunately, manual path tracking is a very time-consuming task and the resulting path depends a lot on the experience of the operator. This severely limits the applicability of the path-based visualization and inspection methods. We have developed an automatic path tracker for virtual endoscopy based on the minimal cost path algorithm described in Deschamps and Cohen [1]. In this paper, we briefly summarize the minimal cost path method and its implementation into an automatic path tracker tool. We also describe the results of a multiuser study, where we measured the speed and operator dependence of the automated path tracker.

9732261 Automatic path tracking using linear quadratic control theory - control method for a curved path Hiroyuki Furusho, Hiroshi Mour (Nissan Motor Co., Ltd.)

9732261 Automatic path tracking using linear quadratic control theory - control method for a curved path Hiroyuki Furusho, Hiroshi Mour (Nissan Motor Co., Ltd.)

Fuzzy supervisory path tracking of mobile reports

In this paper a new method for automatic path tracking of mobile robots and autonomous vehicles is proposed. The paper also includes the application to RAM-1, a new mobile robot testbed designed and built for research and applications in indoor and outdoor industrial enviroments. The method generates the appropriate vehicle steering angle command by combining fuzzy logic with the geometric pure-pursuit technique and the generalized predictive control method. In the proposed fuzzy path-tracking strategy the control parameters of these methods are inferred automatically in real time from the characteristics of the current segment of the path to follow, the vehicle's velocity and its current relative position and orientation.

Fuzzy Supervisory Path Tracking of Mobile Robots

In this paper a new method for automatic path tracking of mobile robots and autonomous vehicles is proposed. The paper also includes the application to RAM-1, a new mobile robot tesbed designed and built for research and applications in indoor and outdoor industrial enviroments. The methods generates the appropiated vehicle's steering angle command by combining fuzzy logic with the geometric pure-pursuit technique and the generalized predictive control method. In the proposed fuzzy path tracking strategy the control parameters of these methods are inferred automatically in real time from the characteristics of the current segment of the path to follow, the vehicle's velocity and its current relative position and orientation