A Hybrid Fireworks Algorithm to Navigation and Mapping

Author(s):  
Tingjun Lei ◽  
Chaomin Luo ◽  
John E. Ball ◽  
Zhuming Bi

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.

2009 ◽  
Vol 26 (2) ◽  
pp. 212-240 ◽  
Author(s):  
Michael W. Otte ◽  
Scott G. Richardson ◽  
Jane Mulligan ◽  
Gregory Grudic

2021 ◽  
Vol 13 (21) ◽  
pp. 4216
Author(s):  
Piotr Duszak ◽  
Barbara Siemiątkowska ◽  
Rafał Więckowski

The paper addresses the problem of mobile robots’ navigation using a hexagonal lattice. We carried out experiments in which we used a vehicle equipped with a set of sensors. Based on the data, a traversable map was created. The experimental results proved that hexagonal maps of an environment can be easily built based on sensor readings. The path planning method has many advantages: the situation in which obstacles surround the position of the robot or the target is easily detected, and we can influence the properties of the path, e.g., the distance from obstacles or the type of surface can be taken into account. A path can be smoothed more easily than with a rectangular grid.


Author(s):  
Prases K. Mohanty ◽  
Dayal R. Parhi

In this article a new optimal path planner for mobile robot navigation based on invasive weed optimization (IWO) algorithm has been addressed. This ecologically inspired algorithm is based on the colonizing property of weeds and distribution. A new fitness function has been formed between robot to goal and obstacles, which satisfied the conditions of both obstacle avoidance and target seeking behavior in robot present in the environment. Depending on the fitness function value of each weed in the colony the robot that avoids obstacles and navigating towards goal. The optimal path is generated with this developed algorithm when the robot reaches its destination. The effectiveness, feasibility, and robustness of the proposed navigational algorithm has been performed through a series of simulation and experimental results. The results obtained from the proposed algorithm has been also compared with other intelligent algorithms (Bacteria foraging algorithm and Genetic algorithm) to show the adaptability of the developed navigational method. Finally, it has been concluded that the proposed path planning algorithm can be effectively implemented in any kind of complex environments.


2013 ◽  
Vol 2 (3) ◽  
pp. 729-748 ◽  
Author(s):  
Marco Pala ◽  
Nafiseh Eraghi ◽  
Fernando López-Colino ◽  
Alberto Sanchez ◽  
Angel de Castro ◽  
...  

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