Research on obstacle avoidance strategy of USV based on improved grid method

The concept of path planning and collision avoidance are two of the most common theories applied for designing and developing in advanced autonomous robotics applications. NI LabView makes it possible to implement real-time processor for obstacle avoidance. The obstacle avoidance strategy ensures that the robot whenever senses the obstacle stops without being collided and moves freely when path is free, but sometimes there exists a probability that once the path is found free and the robot starts moving, then within a fraction of milliseconds, the robot again sense the obstacle and it stops. This continuous swing of stop and run within a very small period of time may cause heavy burden on the system leading to malfunctioning of the components of the system. This paper deals with overcoming this drawback in a way that even after the robot calculates the path is free then also it will wait for a specific amount of time before running it. So as to confirm that if again the sensor detects the obstacle within that specified period then robot don’t need to transit its state suddenly thus avoiding continuous transition of run and stop. Thus it reduces the heavy burden on the system.

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Socially-Aware Reactive Obstacle Avoidance Strategy Based on Limit Cycle

IEEE Robotics and Automation Letters ◽

10.1109/lra.2020.2976302 ◽

2020 ◽

Vol 5 (2) ◽

pp. 3251-3258 ◽

Cited By ~ 1

Author(s):

Manuel Boldrer ◽

Marco Andreetto ◽

Stefano Divan ◽

Luigi Palopoli ◽

Daniele Fontanelli

Keyword(s):

Limit Cycle ◽

Obstacle Avoidance ◽

Avoidance Strategy

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Metal Rubber Blank Automatic Laying Obstacle Avoidance Strategy

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/252/2/022044 ◽

2019 ◽

Vol 252 ◽

pp. 022044

Author(s):

Jiaxiong Xu ◽

Baotong Lu ◽

Ergang Ma ◽

Ruina Jin ◽

Xueheng Cui ◽

...

Keyword(s):

Obstacle Avoidance ◽

Metal Rubber ◽

Avoidance Strategy

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Path planning of lunar robot based on dynamic adaptive ant colony algorithm and obstacle avoidance

International Journal of Advanced Robotic Systems ◽

10.1177/1729881419898979 ◽

2020 ◽

Vol 17 (3) ◽

pp. 172988141989897 ◽

Cited By ~ 1

Author(s):

Shinan Zhu ◽

Weiyi Zhu ◽

Xueqin Zhang ◽

Tao Cao

Keyword(s):

Path Planning ◽

Obstacle Avoidance ◽

Potential Field ◽

Ant Colony Algorithm ◽

Global Search ◽

Convergence Speed ◽

Ant Colony ◽

Local Optimum ◽

Adaptive Potential ◽

Avoidance Strategy

Path planning of lunar robots is the guarantee that lunar robots can complete tasks safely and accurately. Aiming at the shortest path and the least energy consumption, an adaptive potential field ant colony algorithm suitable for path planning of lunar robot is proposed to solve the problems of slow convergence speed and easy to fall into local optimum of ant colony algorithm. This algorithm combines the artificial potential field method with ant colony algorithm, introduces the inducement heuristic factor, and adjusts the state transition rule of the ant colony algorithm dynamically, so that the algorithm has higher global search ability and faster convergence speed. After getting the planned path, a dynamic obstacle avoidance strategy is designed according to the predictable and unpredictable obstacles. Especially a geometric method based on moving route is used to detect the unpredictable obstacles and realize the avoidance of dynamic obstacles. The experimental results show that the improved adaptive potential field ant colony algorithm has higher global search ability and faster convergence speed. The designed obstacle avoidance strategy can effectively judge whether there will be collision and take obstacle avoidance measures.

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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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