Velocity potential approach to path planning for avoiding moving obstacles

Path planning is one of the most important aspects for ambulance driving. A local dynamic path planning method based on the potential field theory is presented in this paper. The potential field model includes two components—repulsive potential and attractive potential. Repulsive potential includes road potential, lane potential and obstacle potential. Considering the driving distinction between an ambulance and a regular vehicle, especially in congested traffic, an adaptive potential function for a lane line is constructed in association with traffic conditions. The attractive potential is constructed with target potential, lane-velocity potential and tailgating potential. The design of lane-velocity potential is to characterize the influence of velocity on other lanes so as to prevent unnecessary lane-changing behavior for the sake of time-efficiency. The results obtained from simulation demonstrate that the proposed method yields a good performance for ambulance driving in an urban area, which can provide support for designing an ambulance support system for the ambulance personnel and dispatcher.

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On line moving obstacles avoidance by velocity potential field

Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393) ◽

10.1109/wcica.2000.863448 ◽

2002 ◽

Author(s):

Zhao Yiwen ◽

Tan Dalong

Keyword(s):

Potential Field ◽

Velocity Potential ◽

Moving Obstacles ◽

On Line

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A fuzzy potential approach with the cache genetic learning algorithm for robot path planning

1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century ◽

10.1109/icsmc.1995.537806 ◽

2002 ◽

Author(s):

Kun Hsiang Wu ◽

Chin Hsing Chen ◽

Jiann Der Lee

Keyword(s):

Path Planning ◽

Learning Algorithm ◽

Robot Path Planning ◽

Potential Approach ◽

Robot Path

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Path planning and robust fuzzy output-feedback control for unmanned ground vehicles with obstacle avoidance

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

10.1177/0954407020978319 ◽

2020 ◽

pp. 095440702097831

Author(s):

Yimin Chen ◽

Chuan Hu ◽

Yechen Qin ◽

Mingjun Li ◽

Xiaolin Song

Keyword(s):

Feedback Control ◽

Path Planning ◽

Obstacle Avoidance ◽

Output Feedback ◽

Output Feedback Control ◽

Unmanned Ground Vehicles ◽

Ground Vehicles ◽

Velocity Signal ◽

Moving Obstacles ◽

Avoidance Strategy

Obstacle avoidance strategy is important to ensure the driving safety of unmanned ground vehicles. In the presence of static and moving obstacles, it is challenging for the unmanned ground vehicles to plan and track the collision-free paths. This paper proposes an obstacle avoidance strategy consists of the path planning and the robust fuzzy output-feedback control. A path planner is formed to generate the collision-free paths that avoid static and moving obstacles. The quintic polynomial curves are employed for path generation considering computational efficiency and ride comfort. Then, a robust fuzzy output-feedback controller is designed to track the planned paths. The Takagi–Sugeno (T–S) fuzzy modeling technique is utilized to handle the system variables when forming the vehicle dynamic model. The robust output-feedback control approach is used to track the planned paths without using the lateral velocity signal. The proposed obstacle avoidance strategy is validated in CarSim® simulations. The simulation results show the unmanned ground vehicle can avoid the static and moving obstacles by applying the designed path planning and robust fuzzy output-feedback control approaches.

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