Collaborative Scheduling of Algorithms for Path Planning of Unmanned Systems

Title:Collaborative Scheduling of Algorithms for Path Planning of Unmanned Systems

Volume: 1 Issue: 3

Author(s): Ying Li, Chubing Guo, Jianshe Wu*, Xin Zhang, Jian Gao, Kai Zhang and Yuqian Wang

Affiliation:

• The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, School of Artificial Intelligence, Xidian University, Xi’an 710071,China

Keywords: Unmanned systems, A* algorithm, path planning, algorithmic collaborative, features of algorithms, representationof algorithms.

Abstract: Background: Unmanned systems have been widely used in multiple fields. Many algorithms have been proposed to solve path planning problems. Each algorithm has its advantages and defects and cannot adapt to all kinds of requirements. An appropriate path planning method is needed for various applications.

Objective: To select an appropriate algorithm swiftly in the given application. This could be helpful for improving the efficiency of path planning for unmanned systems.

Methods: This paper proposes to represent and quantify the features of algorithms based on the physical indicators of results. At the same time, an algorithmic collaborative scheme is developed to search the appropriate algorithm according to the requirement of the application. As an illustration of the scheme, four algorithms, including the A-star (A*) algorithm, reinforcement learning, genetic algorithm, and ant colony optimization algorithm, are implemented in the representation of their features.

Results: In different simulations, the algorithmic collaborative scheme can select an appropriate algorithm in a given application based on the representation of algorithms. Hence, the algorithm could plan a feasible and effective path.

Conclusion: An algorithmic collaborative scheme is proposed, which is based on the representation of algorithms and requirement of the application. The simulation results prove the feasibility of the scheme and the representation of algorithms.

Cite this article as:

Li Ying , Guo Chubing , Wu Jianshe*, Zhang Xin, Gao Jian , Zhang Kai and Wang Yuqian, Collaborative Scheduling of Algorithms for Path Planning of Unmanned Systems, Current Chinese Science 2021; 1 (3) . https://dx.doi.org/10.2174/2210298101666210211094253

DOI https://dx.doi.org/10.2174/2210298101666210211094253	Print ISSN 2210-2981
Publisher Name Bentham Science Publisher	Online ISSN 2210-2914