Avoiding Local Minima for Path Planning Quadrotor Based on Modified Potential Field

2018 ◽  
Vol 11 (4) ◽  
pp. 146
Author(s):  
Iswanto Iswanto
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Local Minima

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.

Path Planning Based on Fuzzy Decision Trees and Potential Field

2016 ◽  
Vol 6 (1) ◽  
pp. 212 ◽  
Author(s):  
Iswanto Iswanto ◽  
Oyas Wahyunggoro ◽  
Adha Imam Cahyadi
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Potential Field ◽  
Planning Problem ◽  
Local Minima ◽  
Fuzzy Decision ◽  
Fuzzy Logic Algorithm ◽  
Planning Decision ◽  
Fuzzy Decision Trees ◽  
Available Information

The fuzzy logic algorithm is an artificial intelligence algorithm that uses mathematical logic to solve to by the data value inputs which are not precise in order to reach an accurate conclusion. In this work, Fuzzy decision tree (FDT) has been designed to solve the path planning problem by considering all available information and make the most appropriate decision given by the inputs. The FDT is often used to make a path planning decision in graph theory. It has been applied in the previous researches in the field of robotics, but it still shows drawbacks in that the robot will stop at the local minima and is not able to find the shortest path. Hence, this paper combines the FDT algorithm with the potential field algorithm. The potential field algorithm provides weight to the FDT algorithm which enables the robot to successfully avoid the local minima and find the shortest path.

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.

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.

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 Mobile Robot Path Planning Using Polyclonal-Based Artificial Immune Network

2013 ◽  
Vol 2013 ◽  
pp. 1-13
Author(s):  
Lixia Deng ◽  
Xin Ma ◽  
Jason Gu ◽  
Yibin Li
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Immune Network ◽  
Local Minima ◽  
Robot Path Planning ◽  
Artificial Immune ◽  
Artificial Immune Network ◽  
Robot Path

Polyclonal based artificial immune network (PC-AIN) is utilized for mobile robot path planning. Artificial immune network (AIN) has been widely used in optimizing the navigation path with the strong searching ability and learning ability. However, artificial immune network exists as a problem of immature convergence which some or all individuals tend to the same extreme value in the solution space. Thus, polyclonal-based artificial immune network algorithm is proposed to solve the problem of immature convergence in complex unknown static environment. Immunity polyclonal algorithm (IPCA) increases the diversity of antibodies which tend to the same extreme value and finally selects the antibody with highest concentration. Meanwhile, immunity polyclonal algorithm effectively solves the problem of local minima caused by artificial potential field during the structure of parameter in artificial immune network. Extensive experiments show that the proposed method not only solves immature convergence problem of artificial immune network but also overcomes local minima problem of artificial potential field. So, mobile robot can avoid obstacles, escape traps, and reach the goal with optimum path and faster convergence speed.

scholarly journals A Novel of Repulsive Function on Artificial Potential Field for Robot Path Planning

2016 ◽  
Vol 6 (6) ◽  
pp. 3262
Author(s):  
H. H. Triharminto ◽  
O. Wahyunggoro ◽  
T. B. Adji ◽  
A. I. Cahyadi ◽  
I. Ardiyanto
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Local Minima ◽  
Robot Path Planning ◽  
Total Potential ◽  
Goal Condition ◽  
Global Optima ◽  
Repulsive Forces ◽  
Robot Path

<p>In this paper, the issue of local minima associated with GNRON (Goal Nonreachable with Obstacles Nearby) has been solved on the Artificial Potential Field (APF) for robot path planning. A novel of repulsive potential function is proposed to solve the problem. The consideration of surrounding repulsive forces gives a trigger to escape from the local mi- nima. Addition of signum function on the repulsive force which considers relative distance between the robot and the goal ensures that the goal position is the global optima of the total potential. Simulation conducted to prove that the proposed algorithm can solve GNRON and local minima problem on APF. Scenario of each simulation set in different type of obs- tacle and goal condition. The results show that the proposed method is able to handle local minima and GNRON problem.</p>

scholarly journals Path Planning Based on Fuzzy Decision Trees and Potential Field

2016 ◽  
Vol 6 (1) ◽  
pp. 212
Author(s):  
Iswanto Iswanto ◽  
Oyas Wahyunggoro ◽  
Adha Imam Cahyadi
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Potential Field ◽  
Planning Problem ◽  
Local Minima ◽  
Fuzzy Decision ◽  
Fuzzy Logic Algorithm ◽  
Planning Decision ◽  
Fuzzy Decision Trees ◽  
Available Information

The fuzzy logic algorithm is an artificial intelligence algorithm that uses mathematical logic to solve to by the data value inputs which are not precise in order to reach an accurate conclusion. In this work, Fuzzy decision tree (FDT) has been designed to solve the path planning problem by considering all available information and make the most appropriate decision given by the inputs. The FDT is often used to make a path planning decision in graph theory. It has been applied in the previous researches in the field of robotics, but it still shows drawbacks in that the robot will stop at the local minima and is not able to find the shortest path. Hence, this paper combines the FDT algorithm with the potential field algorithm. The potential field algorithm provides weight to the FDT algorithm which enables the robot to successfully avoid the local minima and find the shortest path.

A Novel of Repulsive Function on Artificial Potential Field for Robot Path Planning

2016 ◽  
Vol 6 (6) ◽  
pp. 3262
Author(s):  
H. H. Triharminto ◽  
O. Wahyunggoro ◽  
T. B. Adji ◽  
A. I. Cahyadi ◽  
I. Ardiyanto
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Local Minima ◽  
Robot Path Planning ◽  
Total Potential ◽  
Goal Condition ◽  
Global Optima ◽  
Repulsive Forces ◽  
Robot Path

<p>In this paper, the issue of local minima associated with GNRON (Goal Nonreachable with Obstacles Nearby) has been solved on the Artificial Potential Field (APF) for robot path planning. A novel of repulsive potential function is proposed to solve the problem. The consideration of surrounding repulsive forces gives a trigger to escape from the local mi- nima. Addition of signum function on the repulsive force which considers relative distance between the robot and the goal ensures that the goal position is the global optima of the total potential. Simulation conducted to prove that the proposed algorithm can solve GNRON and local minima problem on APF. Scenario of each simulation set in different type of obs- tacle and goal condition. The results show that the proposed method is able to handle local minima and GNRON problem.</p>

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