Enhancing path tracking performance by using haptic shared steering control combined with DYC

2016 ◽  
pp. 49-54
Author(s):  
S. Inoue ◽  
H. Inoue ◽  
T. Ozawa ◽  
P. Raksincharoensak ◽  
M. Nagai
Keyword(s):  
Path Tracking ◽  
Tracking Performance ◽  
Steering Control

Experimental Validations on Vision-Based Path Tracking With Preview Four Wheel Steering Control

2019 ◽  
Author(s):  
Yansong Peng ◽  
Fengchen Wang ◽  
Saikrishna Gurumoorthy ◽  
Yan Chen ◽  
Mutian Xin
Keyword(s):  
Tracking Control ◽  
Low Cost ◽  
Experimental Tests ◽  
Front Wheel ◽  
Path Tracking ◽  
Steering Control ◽  
Tracking Errors ◽  
The Road ◽  
Experimental Validations ◽  
Lateral Offset

Abstract In this paper, a vision-based path-tracking control strategy using four-wheel steering (4WS) is experimentally investigated via an automated ground vehicle (AGV). A low-cost monocular camera is used to continuously perceive the upcoming lane boundaries via capturing the preview road image frames. Based on the applied image processing algorithms, the vehicle lateral offset error with respect to the road center line and the heading angle error with respect to the road curvature are calculated in real time for the control purpose. The 4WS path-tracking controller is designed to minimize the two path-tracking errors of the AGV. The AGV with the 4WS system is utilized to perform the experimental tests on road to validate the path-tracking control design. For comparison, the road test is also conducted for the path-tracking control with only the front wheel steering. The experimental results show that the proposed 4WS is able to achieve better path-tracking performance.

Human-Centered Design of a Spine Biopsy Simulator and the Effects of Visual and Force Feedback on Path-Tracking Performance

2000 ◽  
Vol 9 (4) ◽  
pp. 337-349 ◽  
Author(s):  
Corinna Lathan ◽  
Kevin Cleary ◽  
Laura Traynor
Keyword(s):  
Time Delay ◽  
Visual Feedback ◽  
Task Analysis ◽  
Human Performance ◽  
Force Feedback ◽  
Spatial Reasoning ◽  
Path Tracking ◽  
Tracking Performance ◽  
Tissue Samples ◽  
Technological Intervention

Computed tomography (CT)-directed needle biopsies are routinely performed to gather tissue samples near the spine. As currently practiced, this procedure requires a great deal of spatial reasoning, skill, and training on the part of the interventional radiologist. Our goal was to evaluate the procedure through a task analysis and to make recommendations as to how the procedure could be improved through technological intervention. To this end, a spine biopsy surgical simulator was developed to mimic the current procedure and to serve as a development testbed for procedure innovation. Our methods for looking at the biopsy procedure itself included a task analysis (which produces a detailed list of tasks needed to complete a goal, their order, and time to completion) and an evaluation of human performance measures related to our simulator interface. Experiments were run to examine the effects of force and visual feedback on path-tracking performance and to determine the effects of time delay in the visual feedback on path-tracking performance. Force feedback improved performance in the conditions with visual feedback and in the conditions with visual feedback and time delay.

A hierarchical adaptive control framework of path tracking and roll stability for intelligent heavy vehicle with MPC

2020 ◽  
Vol 234 (13) ◽  
pp. 2933-2946
Author(s):  
Yantao Tian ◽  
Kai Huang ◽  
Xuanhao Cao ◽  
Yulong Liu ◽  
Xuewu Ji
Keyword(s):  
Adaptive Control ◽  
Cooperative Control ◽  
Path Tracking ◽  
Control Mode ◽  
Steering Wheel ◽  
Change Scenario ◽  
Heavy Vehicle ◽  
Steering Control ◽  
Control Framework ◽  
Conflicting Objectives

Roll stability is a major concern in the path tracking process of intelligent heavy vehicles in emergency steering maneuvers. Due to the coupling of lateral and roll motions of heavy vehicle, steering actions for path tracking may come into conflict with that for roll stability. In this paper, a hierarchical adaptive control framework composed of a supervisor, an upper controller and a lower controller is developed to mediate conflicting objectives of path tracking and roll stability via steering control. In the supervisor, path tracking control mode or cooperative control mode of path tracking and roll stability is determined by the predicted rollover index, and a weight function is introduced to balance the control objectives of path tracking and roll stability in cooperative control mode. Then, in order to achieve multi-objective real-time optimization, model predictive control with varying optimization weights is used in the upper controller to calculate the desired front steer angle. The lower controller which integrates the real electrically assisted hydraulic steering system based on Proportional-Integral-Derivative control is designed to control steering wheel angle. Simulation and hardware-in-loop implementation results in double lane change scenario show that the proposed hierarchical adaptive control framework can enhance roll stability in emergency steering maneuvers while keeping the accuracy of path tracking for intelligent heavy vehicle within an acceptable range.

Evaluation of Path Tracking Performance of a Self-driving Tracked Vehicle

2021 ◽  
Vol 45 (12) ◽  
pp. 1167-1176
Author(s):  
Jun Ha Sohn ◽  
Chang-Ho Lee ◽  
Yong-Joo Kim ◽  
Sung-Soo Kim
Keyword(s):  
Path Tracking ◽  
Tracking Performance ◽  
Tracked Vehicle

scholarly journals Steering control based on model predictive control for obstacle avoidance of unmanned ground vehicle

2020 ◽  
Vol 53 (3-4) ◽  
pp. 501-518
Author(s):  
Chaofang Hu ◽  
Lingxue Zhao ◽  
Lei Cao ◽  
Patrick Tjan ◽  
Na Wang
Keyword(s):  
Path Planning ◽  
Model Predictive Control ◽  
Obstacle Avoidance ◽  
Predictive Control ◽  
Path Tracking ◽  
Unmanned Ground Vehicle ◽  
Steering Control ◽  
Steering Angle ◽  
Ground Vehicle ◽  
Tracking Controller

In this paper, a strategy based on model predictive control consisting of path planning and path tracking is designed for obstacle avoidance steering control problem of the unmanned ground vehicle. The path planning controller can reconfigure a new obstacle avoidance reference path, where the constraint of the front-wheel-steering angle is transformed to formulate lateral acceleration constraint. The path tracking controller is designed to realize the accurate and fast following of the reconfigured path, and the control variable of tracking controller is steering angle. In this work, obstacles are divided into two categories: static and dynamic. When the decision-making system of the unmanned ground vehicle determines the existence of static obstacles, the obstacle avoidance path will be generated online by an optimal path reconfiguration based on direct collocation method. In the case of dynamic obstacles, receding horizon control is used for real-time path optimization. To decrease online computation burden and realize fast path tracking, the tracking controller is developed using the continuous-time model predictive control algorithm, where the extended state observer is combined to estimate the lumped disturbances for strengthening the robustness of the controller. Finally, simulations show the effectiveness of the proposed approach in comparison with nonlinear model predictive control, and the CarSim simulation is presented to further prove the feasibility of the proposed method.

scholarly journals A Path Tracking Method for Autonomous Rice Drill Seeder in Paddy Fields

2018 ◽  
Vol 220 ◽  
pp. 04004
Author(s):  
Yan Zhang ◽  
Yanming Li ◽  
Yixiang Huang ◽  
Xiangpeng Liu ◽  
Chengliang Liu
Keyword(s):  
Control Model ◽  
Path Tracking ◽  
Tracking Algorithm ◽  
Paddy Fields ◽  
Steering Control ◽  
Lateral Deviation ◽  
Angle Deviation ◽  
Heading Angle ◽  
The Mean ◽  
Path Tracking Algorithm

For the purpose of overcoming the obstacles in application of autonomous rice drill seeder in paddy fields, a path tracking algorithm with high accuracy used for steering control during straight traveling in uneven muddy paddy fields is introduced in this paper. Combining lateral deviation and heading angle deviation as feedback, a nonlinear steering control model is developed in the algorithm. To avoid the position error caused by incline, the influence brought by the roll angle and the pitch angle of the vehicle on position coordinates are taken into account when the vehicle is on a slant. The experiments carried out in arable paddy fields show that the mean absolute lateral deviation of the algorithm was less than 2.9 centimeters and the heading angle deviation was less than 0.03°. The path tracking algorithm is able to meet the required precision for autonomous rice drill seeder in paddy fields of China.

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