Robot Path Planning by Generalized Ant Colony Algorithm

2014 ◽  
Vol 494-495 ◽  
pp. 1229-1232 ◽  
Author(s):  
Dai Yuan Zhang ◽  
Peng Fu

For the problem that the searching speed of traditional ant colony algorithm in robot path planning problem is slow, this paper will solve this problem with generalized ant colony algorithm. Generalized ant colony algorithm extends the definition of ant colony algorithm and does more general research for ant colony algorithm. Functional update strategy replaces the parametric algorithm update strategy; it accelerates the convergence speed of ant colony algorithm. Applying the generalized ant colony algorithm to robot path planning problem can improve the searching speed of robots and reduce the cost of convergence time.

Author(s):  
C. Y. Liu ◽  
R. W. Mayne

Abstract This paper considers the problem of robot path planning by optimization methods. It focuses on the use of recursive quadratic programming (RQP) for the optimization process and presents a formulation of the three dimensional path planning problem developed for compatibility with the RQP selling. An approach 10 distance-to-contact and interference calculations appropriate for RQP is described as well as a strategy for gradient computations which are critical to applying any efficient nonlinear programming method. Symbolic computation has been used for general six degree-of-freedom transformations of the robot links and to provide analytical derivative expressions. Example problems in path planning are presented for a simple 3-D robot. One example includes adjustments in geometry and introduces the concept of integrating 3-D path planning with geometric design.


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