Adaptive information feedback particle swarm robot path selecting method based on multiple subgroups and system thereof

Abstract

The invention belongs to the technical field of machine learning, and discloses an adaptive information feedback particle swarm robot path selecting method based on multiple subgroups and a system thereof. Multiple diversity unified defining manners are used for a diversity evaluation strategy, thereby evaluating group diversity from multiple angles. A multiple-subgroup dividing strategy is performed on a particle group through comprehensive analysis of adaptability and spatial angle. Presetting of subgroup number is not required. A wide area searching effect in a dynamic optimizing process can be improved. A sparse processing strategy is utilized for adjusting a distribution condition in the subgroup so that the particles in the subgroup can be far from local central particles in a certain probability, thereby executing a real-time exploration process in a local area and improving diversity level in the subgroup. The adaptive information feedback particle swarm robot path selecting method and the system thereby facilitate fine exploration for a local optimal value and wide-range searching in a global range. Through result analysis on a testing problem, the method and the system according to the invention can be effectively applied in problems of multidirectional dynamic optimization and robot global path planning and further have advantages of simple and applicable method and certain use value.

Description

technical field [0001] The invention belongs to the technical field of machine learning, and in particular relates to a multi-subgroup-based self-adaptive information feedback particle swarm robot path selection method and system. Background technique [0002] With the continuous development and popularization of intelligent optimization technology, robot technology has gradually penetrated into various environments of people's daily life and work, playing an irreplaceable role in many aspects. Especially in many large-scale, high-intensity and complex environments, the use of robots for heavy or persistent work can save material and labor costs to a large extent, and bring direct benefits to enterprises / industries while improving work efficiency. economic profit. In the application process of robot technology, global path planning technology, as a kind of global optimization problem, is a key technology in the research of mobile robot technology, which directly affects the...

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Problems solved by technology

[0005] Although the above-mentioned PSO improved method has achieved certain application effects in robot path planning, the calculation time of this type of algorithm is generally too long, and the change of the environment will easily reduce the search efficiency of the path, and the optimal planning path obtained is often a local optimum. Optimal solution, it is difficult to meet the requirements of real-time path planning

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