A Hybrid Fireworks Algorithm to Navigation and Mapping

Author:

Lei Tingjun1,Luo Chaomin1ORCID,Ball John E.1,Bi Zhuming2

Affiliation:

1. Mississippi State University, USA

2. Purdue University, Fort Wayne, USA

Abstract

In recent years, computer technology and artificial intelligence have developed rapidly, and research in the field of mobile robots has continued to deepen with development of artificial intelligence. Path planning is an essential content of mobile robot navigation of computing a collision-free path between a starting point and a goal. It is necessary for mobile robots to move and maneuver in different kinds of environment with objects and obstacles. The main goal of path planning is to find the optimal path between the starting point and the target position in the minimal possible time. A new firework algorithm (FWA) integrated with a graph theory, Dijkstra's algorithm developed for autonomous robot navigation, is proposed in this chapter. The firework algorithm is improved by a local search procedure that a LIDAR-based local navigator algorithm is implemented for local navigation and obstacle avoidance. The grid map is utilized for real-time intelligent robot mapping and navigation. In this chapter, both simulation and comparison studies of an autonomous robot navigation demonstrate that the proposed model is capable of planning more reasonable and shorter, collision-free paths in non-stationary and unstructured environments compared with other approaches.

Publisher

IGI Global

Reference17 articles.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Digital twin‐based multi‐objective autonomous vehicle navigation approach as applied in infrastructure construction;IET Cyber-Systems and Robotics;2024-03-20

2. Multitask Allocation Framework With Spatial Dislocation Collision Avoidance for Multiple Aerial Robots;IEEE Transactions on Aerospace and Electronic Systems;2022-12

3. Human-Autonomy Teaming-Based Robot Informative Path Planning and Mapping Algorithms with Tree Search Mechanism;2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS);2022-11-17

4. Multi-Robot Directed Coverage Path Planning in Row-based Environments;2022 IEEE Fifth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE);2022-09

5. A Bio-Inspired Neural Network Approach to Robot Navigation and Mapping with Nature-Inspired Algorithms;Lecture Notes in Computer Science;2022

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