Robot path planning based on artificial immune network

2007 ◽  
Author(s):  
Xuanzi Hu ◽  
Cunxi Xie ◽  
Qingui Xu
Keyword(s):  
Path Planning ◽  
Immune Network ◽  
Robot Path Planning ◽  
Artificial Immune ◽  
Artificial Immune Network ◽  
Robot Path

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.

A New Artificial Immune Network Model for Mobile Robot Path Planning

2013 ◽  
Vol 416-417 ◽  
pp. 757-761 ◽  
Author(s):  
Ming Xin Yuan ◽  
Pan Pan Zhang ◽  
Han Yang Li ◽  
Shuai Cheng ◽  
Yi Shen
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Antibody Concentration ◽  
Immune Network ◽  
Robot Path Planning ◽  
Uncertain Environments ◽  
Planning Algorithm ◽  
Immune Network Model ◽  
Path Planning Algorithm ◽  
Robot Path

To solve the mobile robot path planning in uncertain environments, a new path planning algorithm is presented on the basis of the biological immune network. The environment surrounding the robot is taken as the antigen, and the behavior strategy of robot is taken as the antibody. The selection model of antibody concentration is defined based on the Jernes idiotypic immune network hypothesis, and the mobile robot path planning is realized through the selection of the antibody concentration. The simulation of path planning for mobile robot in multi-obstacle environments shows that the robot can find a safe path in complicated environments, which verifies the better adaptivity of proposed planning model. The simulation in dynamic environments shows that the robot can safely avoid all dynamic obstacles, which verifies the better flexility of new algorithm.

A Novel Mutual-coupled Immune Network Algorithm with the Characteristic of Memory for Mobile Robot Path Planning

2013 ◽  
Vol 12 (9) ◽  
pp. 1755-1763 ◽  
Author(s):  
Mingxin Yuan ◽  
Panpan Zhang ◽  
Hanyang Li ◽  
Yafeng Jiang ◽  
Yi Shen
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Immune Network ◽  
Robot Path Planning ◽  
Network Algorithm ◽  
Robot Path

APF-guided adaptive immune network algorithm for robot path planning

2009 ◽  
Vol 3 (2) ◽  
pp. 247-255 ◽  
Author(s):  
Mingxin Yuan ◽  
Sun-an Wang ◽  
Canyang Wu ◽  
Kunpeng Li
Keyword(s):  
Path Planning ◽  
Immune Network ◽  
Robot Path Planning ◽  
Adaptive Immune ◽  
Network Algorithm ◽  
Robot Path

Mobile Robot Path Planning and Research in the Improved Artificial Immune Algorithm

2012 ◽  
Vol 466-467 ◽  
pp. 864-869 ◽  
Author(s):  
Yuan Bin Hou ◽  
Wei Wang ◽  
Xiao Yue Lu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimal Path ◽  
Immune Algorithm ◽  
Initial Population ◽  
Robot Path Planning ◽  
Artificial Immune ◽  
Artificial Immune Algorithm ◽  
Selection Operator ◽  
Robot Path

Aim at local optimal problem in the path planning of mobile robot by artificial immune algorithm, it is proposed that the improved artificial immune algorithm of mobile robot path planning. Based on artificial immunity algorithm, the potential function method of an artificial potential field is used in this algorithm, improving randomness of the initial population of the artificial immune algorithm, then the algorithm make initial population turn to evolutionary operation through crossover, variance and selection operator to get optimum antibody. The simulation results showed that this algorithm is easy to get the optimal path, at the same time, increasing the speed of the path planning, and the length of the optimal path planning is less 28.5% compare with the traditional immune algorithm.

A Novel Immune Network Strategy for Robot Path Planning in Complicated Environments

2010 ◽  
Vol 60 (1) ◽  
pp. 111-131 ◽  
Author(s):  
Mingxin Yuan ◽  
Sun-an Wang ◽  
Canyang Wu ◽  
Naijian Chen
Keyword(s):  
Path Planning ◽  
Immune Network ◽  
Robot Path Planning ◽  
Robot Path
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