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 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 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.

Research of Anti-Collision Method in Robot Path Planning Process

2014 ◽  
Vol 644-650 ◽  
pp. 323-325
Author(s):  
Tao Hua Ma
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Planning Process ◽  
Route Planning ◽  
Artificial Potential Field ◽  
Robot Path Planning ◽  
Fusion Algorithm ◽  
Relationship Model ◽  
Repulsive Forces ◽  
Robot Path

In the research of robot path planning anti-collision method, with the traditional algorithm to plan robot path, the planning processis single, cumbersome and inefficient. To this end, a mobile robot path planning method based on potential field genetic fusion algorithm is proposed to establish the relationship model of different force in artificial potential field, and calculate attractive and repulsive forces applied on robotics in the artificial potential field, according to the attractive and repulsive forces to complete the anti-collision handling in route planning process. Experimental results show that the improved algorithm for anti-collision process in robot path planning, can effectively improve the computational efficiency for the anti-collision, expand its application field and enhance the technicality of anti-collision.

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