Abstract

Pigeon Inspired Optimization (PIO) algorithm is gaining popularity since its development due to faster convergence ability with great efficiencies when compared with other bio-inspired algorithms. The navigation capability of homing pigeons has been precisely used in Pigeon Inspired Optimization algorithm and continuous advancement in existing algorithms is making it more suitable for complex optimization problems in various fields. The main theme of this survey paper is to introduce the basics of PIO along with technical advancements of PIO for the motion planning techniques of dynamic agents. The survey also comprises of findings and limitations of proposed work since its development to help the research scholar around the world for particular algorithm selection especially for motion planning. This survey might be extended up to application based in order to understand the importance of algorithm in future studies.

Highlights

  • The searching ability of homing pigeon is unmatched with other birds as it can be more accurate to achieve the destination despite long distance traveling [1]

  • This study sum up the motion planning techniques based on Pigeon Inspired Optimization (PIO) and its variants of many agents including unmanned aerial vehicles (UAV’s) with the help of findings and limitations

  • PIO is the state of the art optimization algorithm that was initially proposed for aerial robot path planning problems

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Summary

Introduction

The searching ability of homing pigeon is unmatched with other birds as it can be more accurate to achieve the destination despite long distance traveling [1]. Based on the searching ability for global search and route planning in pigeons encourage the researcher to introduce a novel optimization algorithm namely “Pigeon Inspired Optimization (PIO) algorithm” in 2014 for optimal solutions [10]. The unwanted uncertainties and complexities of various agents formed in a group still challenging for many researchers To improve these hurdles proper motion planning of agents required that can reduce the convergence time and enhance stability of the system. This study sum up the motion planning techniques based on PIO and its variants of many agents including unmanned aerial vehicles (UAV’s) with the help of findings and limitations.

State of art
Mechanism
Principle optimization
Pigeon inspired optimization and its variants
Design”
Findings
Conclusion
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