Title :
Planning multiple paths with evolutionary speciation
Author :
C. Hocaoglu;A.C. Sanderson
Author_Institution :
Dept. of Comput. Eng., State Univ. of New York, Stony Brook, NY, USA
Abstract :
This paper demonstrates a new approach to multidimensional path planning that is based on multiresolution path representation, where explicit configuration space computation is not required, and incorporates an evolutionary algorithm for solving the multimodal optimization problem, generating multiple alternative paths simultaneously. The multiresolution path representation reduces the expected search length for the path-planning problem and accordingly reduces the overall computational complexity. Resolution independent constraints due to obstacle proximity and path length are introduced into the evaluation function. The system can be applied for planning paths for mobile robots, assembly, and articulated manipulators. The resulting path-planning system has been evaluated on problems of two, three, four, and six degrees of freedom. The resulting paths are practical, consistent, and have acceptable execution times. The multipath algorithm is demonstrated on a number of 2D path-planning problems.
Keywords :
"Path planning","Computational complexity","Clustering algorithms","Robotics and automation","Multidimensional systems","Evolutionary computation","Mobile robots","Assembly systems","Robotic assembly","Manipulators"
Journal_Title :
IEEE Transactions on Evolutionary Computation
ISSN :
1089-778X;1089-778X
DOI :
10.1109/4235.930309