Abstract

Robots are coming to help us in different harsh environments such as deep sea or coal mine. Waste landfill is the place like these with casualty risk, gas poisoning, and explosion hazards. It is reasonable to use robots to fulfill tasks like burying operation, transportation, and inspection. In these assignments, one important issue is to obtain appropriate paths for robots especially in some complex applications. In this context, a novel hybrid swarm intelligence algorithm, ant colony optimization enhanced by chaos-based particle swarm optimization, is proposed in this article to deal with the path planning problem for landfill inspection robots in Asahikawa, Japan. In chaos-based particle swarm optimization, Chebyshev chaotic sequence is used to generate the random factors for particle swarm optimization updating formula so as to effectively adjust particle swarm optimization parameters. This improved model is applied to optimize and determine the hyper parameters for ant colony optimization. In addition, an improved pheromone updating strategy which combines the global asynchronous feature and “Elitist Strategy” is employed in ant colony optimization in order to use global information more appropriately. Therefore, the iteration number of ant colony optimization invoked by chaos-based particle swarm optimization can be reduced reasonably so as to decrease the search time effectively. Comparative simulation experiments show that the chaos-based particle swarm optimization-ant colony optimization has a rapid search speed and can obtain solutions with similar qualities.

Highlights

  • Waste management plays an import role in environmental protection, energy reuse, sustainable development, and people’s daily life

  • We introduce an improved ant colony optimization (ACO) to solve the traveling salesman problem (TSP), enabling the robot to find the feasible route, travel around the landfill, and fulfill the task appropriately

  • The proposed hybrid chaos-based particle swarm optimization (CPSO)-ACO model is applied to deal with path planning task of landfill inspection robot in Asahikawa, Japan.[53,54]

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Summary

Introduction

Waste management plays an import role in environmental protection, energy reuse, sustainable development, and people’s daily life. ACO parameters are optimized by PSO and classical pheromone updating strategy is used.

Results
Conclusion
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