A Novel Approach for Path Planning Based on Reactive Behavior-Artificial Potential Filed

2014 ◽  
Vol 529 ◽  
pp. 646-649 ◽  
Author(s):  
Long Xiang Yang ◽  
Zai Xin Liu ◽  
Hao Tang
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Optimal Selection ◽  
Local Minima ◽  
Novel Approach ◽  
Reactive Behavior ◽  
Real Time Application

The main objective of this paper is to focus on the local minima and the GNRON issues encountered in path planning by the artificial potential field (APF) method, and propose a novel approach to plan a trajectory adaptive for the environment that the obstacles are randomly distributed. By introducing the ideas of reactive behaviors (RB), the RB-APF method is presented, which combines the efficiency of the APF with the simplicity of the RB, so it can be suitable for real-time application in mobile robots. In this algorithm (RB-APF), the switch conditions and optimal selection equations are reasonably designed with the consideration of the different circumstances of the robot located in. Simulations are presented and the results further demonstrate that the proposed approach is applicable for the environment that obstacles are randomly distributed.

scholarly journals Improved Artificial Potential Field Method Applied for AUV Path Planning

2020 ◽  
Vol 2020 ◽  
pp. 1-21 ◽  
Author(s):  
Xiaojing Fan ◽  
Yinjing Guo ◽  
Hui Liu ◽  
Bowen Wei ◽  
Wenhong Lyu
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Potential Field ◽  
Moving Objects ◽  
Dynamic Environment ◽  
Planning Method ◽  
Artificial Potential Field ◽  
Local Minima ◽  
Field Function ◽  
Time Path

With the topics related to the intelligent AUV, control and navigation have become one of the key researching fields. This paper presents a concise and reliable path planning method for AUV based on the improved APF method. AUV can make the decision on obstacle avoidance in terms of the state of itself and the motion of obstacles. The artificial potential field (APF) method has been widely applied in static real-time path planning. In this study, we present the improved APF method to solve some inherent shortcomings, such as the local minima and the inaccessibility of the target. A distance correction factor is added to the repulsive potential field function to solve the GNRON problem. The regular hexagon-guided method is proposed to improve the local minima problem. Meanwhile, the relative velocity method about the moving objects detection and avoidance is proposed for the dynamic environment. This method considers not only the spatial location but also the magnitude and direction of the velocity of the moving objects, which can avoid dynamic obstacles in time. So the proposed path planning method is suitable for both static and dynamic environments. The virtual environment has been built, and the emulation has been in progress in MATLAB. Simulation results show that the proposed method has promising feasibility and efficiency in the AUV real-time path planning. We demonstrate the performance of the proposed method in the real environment. Experimental results show that the proposed method is capable of avoiding the obstacles efficiently and finding an optimized path.

scholarly journals Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 188 ◽  
Author(s):  
Qing Wu ◽  
Zeyu Chen ◽  
Lei Wang ◽  
Hao Lin ◽  
Zijing Jiang ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Potential Field ◽  
Optimization Method ◽  
Artificial Potential Field ◽  
Planning Time ◽  
Time Dynamic ◽  
Dynamic Path Planning ◽  
Dynamic Path

Mobile robots are becoming more and more widely used in industry and life, so the navigation of robots in dynamic environments has become an urgent problem to be solved. Dynamic path planning has, therefore, received more attention. This paper proposes a real-time dynamic path planning method for mobile robots that can avoid both static and dynamic obstacles. The proposed intelligent optimization method can not only get a better path but also has outstanding advantages in planning time. The algorithm used in the proposed method is a hybrid algorithm based on the beetle antennae search (BAS) algorithm and the artificial potential field (APF) algorithm, termed the BAS-APF method. By establishing a potential field, the convergence speed is accelerated, and the defect that the APF is easily trapped in the local minimum value is also avoided. At the same time, by setting a security scope to make the path closer to the available path in the real environment, the effectiveness and superiority of the proposed method are verified through simulative results.

Mechanical arm obstacle avoidance path planning based on improved artificial potential field method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tianying Xu ◽  
Haibo Zhou ◽  
Shuaixia Tan ◽  
Zhiqiang Li ◽  
Xia Ju ◽  
...  
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Planning Process ◽  
Field Method ◽  
Artificial Potential Field ◽  
Local Minima ◽  
Content Type ◽  
Potential Field Method ◽  
Artificial Potential Field Method

Purpose This paper aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process. Design/methodology/approach In this paper, an improved artificial potential field method is proposed, where the object can leave the local minima point, where the algorithm falls into, while it avoids the obstacle, following a shorter feasible path along the repulsive equipotential surface, which is locally optimized. The whole obstacle avoidance process is based on the improved artificial potential field method, applied during the mechanical arm path planning action, along the motion from the starting point to the target point. Findings Simulation results show that the algorithm in this paper can effectively perceive the obstacle shape in all the selected cases and can effectively shorten the distance of the planned path by 13%–41% with significantly higher planning efficiency compared with the improved artificial potential field method based on rapidly-exploring random tree. The experimental results show that the improved artificial potential field method can effectively plan a smooth collision-free path for the object, based on an algorithm with good environmental adaptability. Originality/value An improved artificial potential field method is proposed for optimized obstacle avoidance path planning of a mechanical arm in three-dimensional space. This new approach aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

scholarly journals A Path Planning Algorithm for a Dynamic Environment Based on Proper Generalized Decomposition

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2245
Author(s):  
Antonio Falcó ◽  
Lucía Hilario ◽  
Nicolás Montés ◽  
Marta C. Mora ◽  
Enrique Nadal
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Potential Field ◽  
Dynamic Environment ◽  
Artificial Potential Field ◽  
Proper Generalized Decomposition ◽  
Partial Differential ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A necessity in the design of a path planning algorithm is to account for the environment. If the movement of the mobile robot is through a dynamic environment, the algorithm needs to include the main constraint: real-time collision avoidance. This kind of problem has been studied by different researchers suggesting different techniques to solve the problem of how to design a trajectory of a mobile robot avoiding collisions with dynamic obstacles. One of these algorithms is the artificial potential field (APF), proposed by O. Khatib in 1986, where a set of an artificial potential field is generated to attract the mobile robot to the goal and to repel the obstacles. This is one of the best options to obtain the trajectory of a mobile robot in real-time (RT). However, the main disadvantage is the presence of deadlocks. The mobile robot can be trapped in one of the local minima. In 1988, J.F. Canny suggested an alternative solution using harmonic functions satisfying the Laplace partial differential equation. When this article appeared, it was nearly impossible to apply this algorithm to RT applications. Years later a novel technique called proper generalized decomposition (PGD) appeared to solve partial differential equations, including parameters, the main appeal being that the solution is obtained once in life, including all the possible parameters. Our previous work, published in 2018, was the first approach to study the possibility of applying the PGD to designing a path planning alternative to the algorithms that nowadays exist. The target of this work is to improve our first approach while including dynamic obstacles as extra parameters.

Predictive Artificial Potential Field Method and its Application on Robot Soccer Path Planning

2011 ◽  
Vol 48-49 ◽  
pp. 840-843 ◽  
Author(s):  
Peng Huang ◽  
Chang Yun Miao ◽  
Li Jin Guo ◽  
Ying Li
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Potential Field ◽  
Field Method ◽  
Artificial Potential Field ◽  
Robot Soccer ◽  
Uncertain Environment ◽  
Field Approach ◽  
Potential Field Method ◽  
Artificial Potential Field Method

This paper presents a new predictive artificial potential field approach for robot soccer path planning under complex and uncertain environment. By predicting and analyzing the future position and attitude of concerned object, the position and attitude of the object is controlled by demonstration algorithm. The proposed method is successfully used in the robor soccer shooting and is realized on the MiroSot 3vs3 simulating platform. Experiment results show that this algorithm has good real-time ability and adaptability to environment.

Path Planning of Mobile Robot Based on Improved Artificial Potential Field Method

2014 ◽  
Vol 644-650 ◽  
pp. 154-157 ◽  
Author(s):  
Su Ying Zhang ◽  
Yan Kai Shen ◽  
Wen Shuai Cui
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Potential Field ◽  
High Efficiency ◽  
Field Method ◽  
Artificial Potential Field ◽  
Local Minima ◽  
Potential Field Method ◽  
Smooth Path ◽  
Artificial Potential Field Method

The artificial potential field method has been extensively used in mobile robot path planning for its characteristics of simpleness, high efficiency, and smooth path. In this paper, to solve the problem of local minima in traditional artificial potential field method, A modified form of repulsion function is proposed. A detour force is added to the repulsion function, the problem of local minima can be solved effectively. In the end, with the help of Matlab software simulating, the result shows that this method is simple and effective.

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