Various heuristic and metaheuristic algorithms were proposed in early 70s. Metaheuristic algorithms are very
simple, flexible, derivation free mechanism and are superior to others conventional optimization techniques. They make use
of domain specific knowledge and is controlled by upper level strategy, they are approximate and usually non deterministic.
This paper proposes a newly developed hybrid metaheuristic algorithm (MACOCS) inspired by the behavior of ants and
cuckoo birds. Path planning is very sensitive issue of mobile robot movement, here developed MACOCS technique is
applied on it to find out collision free optimized path in environment having static and dynamic obstacles both. The results
show that MACOCS provides competent results as compared to modified ACO and Cuckoo Search algorithms. It also
shows that the proposed algorithm can also be successfully applied to any challenging problems with unknown search
Published In:IJCSN Journal Volume 7, Issue 3
Date of Publication : June 2018
Pages : 192-198
Tables : 04
Dr. Sapna Katiyar : Professor, ABES Institute of Technology, Ghaziabad.
In the proposed work motion planning of mobile robot is
considered as an optimization problem. All three
algorithms perform randomly search to find out feasible
route by avoiding all hindrance coming in between the
route without taking large computational time. It employs
ACO as global path planning technique wile CS as local
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