Steering Control and Path Planning of Two-Wheel Vehicle with Hazard Avoidance

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.

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VISION BASED OBSTACLE DETECTION USING ROVER STEREO IMAGES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w13-1471-2019 ◽

2019 ◽

Vol XLII-2/W13 ◽

pp. 1471-1477

Author(s):

Y. Wang ◽

M. Peng ◽

K. Di ◽

W. Wan ◽

Z. Liu ◽

...

Keyword(s):

Path Planning ◽

Image Matching ◽

Three Dimensional ◽

Light Condition ◽

Obstacle Detection ◽

Stereo Images ◽

Localization Accuracy ◽

Hazard Avoidance ◽

Yutu Rover ◽

Topographic Relief

<p><strong>Abstract.</strong> Vision based obstacle detection using stereo images is an essential way for hazard avoidance and path planning in planetary rover missions. However, due to light condition changes and topographic relief, only partial or sparse three-dimensional points may be derived by image matching and triangulation reconstruction, which is not sufficient for recognizing obstacles. In this paper, we developed a strategy to detect obstacles using rover stereo images by combining both image grayscale information and sparse 3D point information. Experiments were carried out using stereo images captured by navigation cameras mounted on the Yutu rover of Chang’e-3 mission. Moreover, how obstacle localization accuracy affected by the parameters are analysed and discussed.</p>

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Integrated path planning and dynamic steering control for autonomous vehicles

10.1109/robot.1986.1087444 ◽

2005 ◽

Cited By ~ 94

Author(s):

B. Krogh ◽

C. Thorpe

Keyword(s):

Path Planning ◽

Autonomous Vehicles ◽

Steering Control ◽

Dynamic Steering

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Driver-behavior-based robust steering control of unmanned driving robotic vehicle with modeling uncertainties and external disturbance

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407019895158 ◽

2020 ◽

Vol 234 (6) ◽

pp. 1585-1596

Author(s):

Gang Chen ◽

ShuHua Su

Keyword(s):

Path Planning ◽

Control Method ◽

Driver Behavior ◽

External Disturbance ◽

Steering Control ◽

Planning Strategy ◽

Human Driver ◽

Modeling Uncertainties ◽

Robotic Vehicle ◽

The Stability

In this paper, a steering robust control method based on professional driver behavior with modeling uncertainties and external disturbance is proposed for an unmanned driving robotic vehicle, to realize the accurate and stable steering control like a professional human driver. An unmanned driving robotic vehicle nonlinear dynamics model considering modeling uncertainties and external disturbance is established. A driver behavior model composed of an adaptive preview model, a driver path planning model, and a driver desired yaw rate model is established, with the influences on preview time and driver path planning strategy, respectively. On the basis of this, a robust steering controller based on professional driver behavior is presented, by taking road information, driver reaction delay time, and vehicle driving status as inputs and the servo motor rotation angle of the steering mechanical arm as output. The stability of the control system with modeling uncertainties and external disturbance is proved. A comparison of the analysis results of simulation and experiment among the proposed control method, other existing control methods, and professional human driver demonstrates the effectiveness of the proposed method.

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