scholarly journals Mobile Robot Path Planning Method Using Firefly Algorithm for 3D Sphere Dynamic & Partially Known Environment

2018 ◽  
Vol 26 (7) ◽  
pp. 309-320 ◽  
Author(s):  
Alia Karim Abdul Hassan ◽  
Duaa Jaafar Fadhil
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Free Path ◽  
Firefly Algorithm ◽  
Three Dimensional ◽  
Planning Method ◽  
Dimensional Sphere ◽  
Robot Path Planning ◽  
Safe Navigation ◽  
Robot Path

 In this paper, a new method is proposed to solve the problem of path planning for a mobile robot in a dynamic-partially knew three-dimensional sphere environment by using a modified version of the Firefly Algorithm that successfully finds near optimal and collision-free path while maintaining quick, easy and completely safe navigation throughout the path to the goal.

A new path planning method of mobile robot based on adaptive dynamic firefly algorithm

2020 ◽  
Vol 34 (29) ◽  
pp. 2050322
Author(s):  
Guanghui Xu ◽  
Ting-Wei Zhang ◽  
Qiang Lai ◽  
Jian Pan ◽  
Bo Fu ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
High Performance ◽  
Firefly Algorithm ◽  
Optimal Solution ◽  
Robot Path Planning ◽  
Adaptive Parameters ◽  
Local Optimal Solution ◽  
Reaction Speed ◽  
Robot Path

Path planning has always been a hot topic in the field of mobile robot research. At present, the mainstream issues of the mobile robot path planning are combined with the swarm intelligence algorithms. Among them, the firefly algorithm is more typical. The firefly algorithm has the advantages of simple concepts and easy implementation, but it also has the disadvantages of being easily trapped into a local optimal solution, with slow convergence speed and low accuracy. To better combine the path planning of mobile robot with firefly algorithm, this paper studies the optimization firefly algorithm for the path planning of mobile robot. By using the strategies of optimizing the adaptive parameters in the firefly algorithm, an adaptive firefly algorithm is designed to solve the problem that the firefly algorithm is easy to get into the local optimal solution and improves the performance of firefly algorithm. The optimized algorithm with high performance can improve the computing ability and reaction speed of the mobile robot in the path planning. Finally, the theoretical and experimental results have verified the effectiveness and superiority of the proposed algorithm, which can meet the requirements of the mobile robot path planning.

A Mobile Robot Path Planning Method Based on Safe Pathfinding Guidance

2021 ◽  
Author(s):  
Tong Bie ◽  
Xiaoqing Zhu ◽  
Xiaoli Li ◽  
Xiaogang Ruan
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Planning Method ◽  
Robot Path Planning ◽  
Robot Path

scholarly journals Mobile robot path planning in dynamic environment based on cuckoo optimization algorithm

2019 ◽  
Vol 16 (2) ◽  
pp. 172988141983957 ◽  
Author(s):  
Seyedhadi Hosseininejad ◽  
Chitra Dadkhah
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Free Path ◽  
Optimization Algorithm ◽  
Dynamic Environment ◽  
Planning Problem ◽  
Robot Path Planning ◽  
Cuckoo Optimization Algorithm ◽  
Starting Point ◽  
Robot Path

Nowadays, the usage of autonomous mobile robots that fulfill various activities in enormous number of applications without human’s interference in a dynamic environment are thriving. A dynamic environment is the robot’s environment which is comprised of some static obstacles as well as several movable obstacles that their quantity and location change randomly through the time. Efficient path planning is one the significant necessities of these kind of robots to do their tasks effectively. Mobile robot path planning in a dynamic environment is finding a shortest possible path from an arbitrary starting point toward a desired goal point which needs to be safe (obstacle avoidance) and smooth as well as possible. To achieve this target, simultaneously satisfying a collection of certain constraints including the shortest, smooth, and collision free path is required. Therefore, this issue can be considered as an optimization problem, consequently solved via optimization algorithms. In this article, a new method based on cuckoo optimization algorithm is proposed for solving the mobile robot path planning problem in a dynamic environment. Furthermore, to diminish the computational complexity, the feature vector is also optimized (i.e. reduced in dimension) via a new proposed technique. The simulation results show the performance of proposed algorithm in finding a short, safe, smooth, and collision free path in different environment conditions.

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