scholarly journals Hybrid metaheuristic approach for robot path planning in dynamic environment

2021 ◽  
Vol 10 (4) ◽  
pp. 2152-2162
Author(s):  
Lina Basem Amar ◽  
Wesam M. Jasim
Keyword(s):  
Path Planning ◽  
Hybrid Algorithm ◽  
Optimization Problem ◽  
Dynamic Environment ◽  
Target Point ◽  
Complex Environments ◽  
Robot Path Planning ◽  
Moving Obstacles ◽  
Starting Point ◽  
Robot Path

Recently robots have gained great attention due to their ability to operate in dynamic and complex environments with moving obstacles. The path planning of a moving robot in a dynamic environment is to find the shortest and safe possible path from the starting point towards the desired target point. A dynamic environment is a robot's environment that consists of some static and moving obstacles. Therefore, this problem can be considered as an optimization problem and thus it is solved via optimization algorithms. In this paper, three approaches for determining the optimal pathway of a robot in a dynamic environment were proposed. These approaches are; the particle swarming optimization (PSO), ant colony optimization (ACO), and hybrid PSO and ACO. These used to carry out the path planning tasks effectively. A set of certain constraints must be met simultaneously to achieve the goals; the shortest path, the least time, and free from collisions. The results are calculated for the two algorithms separately and then that of the hybrid algorithm is calculated. The effectiveness and superiority of the hybrid algorithm were verified on both PSO and ACO algorithms.

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.

Path Planning for Nonholonomic Mobile Robot in Dynamic Environment

2013 ◽  
Vol 462-463 ◽  
pp. 771-774
Author(s):  
Liang Kang ◽  
Lian Cheng Mao
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Dynamic Environment ◽  
Adaptive Mesh ◽  
Equation Model ◽  
Robot Path Planning ◽  
Nonholonomic Mobile Robot ◽  
Trajectory Tracking Controller ◽  
Fluid Diffusion ◽  
Robot Path

Based on introduction of the fluid diffusion energy, the model for path planning is presented. The adaptive mesh is used to solve the equation model for path planning. Based on the dynamic model and kinematic constraints of the nonholonomic mobile robot, a trajectory tracking controller is designed. Theory and calculation results prove that, as a new method for mobile robot path planning, the equation of the fluid diffusion energy for nonholonomic mobile robot path planning is feasible and effective.

scholarly journals Mobile Robot Path Planning Based on a Generalized Wavefront Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Sifan Wu ◽  
Yu Du ◽  
Yonghua Zhang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Path Length ◽  
Computation Time ◽  
Target Point ◽  
Multiple Target ◽  
Robot Path Planning ◽  
Practical Applications ◽  
Real Time Applications ◽  
Robot Path

This study develops a generalized wavefront algorithm for conducting mobile robot path planning. The algorithm combines multiple target point sets, multilevel grid costs, logarithmic expansion around obstacles, and subsequent path optimization. The planning performances obtained with the proposed algorithm, the A∗ algorithm, and the rapidly exploring random tree (RRT) algorithm optimized using a Bézier curve are compared using simulations with different grid map environments comprising different numbers of obstacles with varying shapes. The results demonstrate that the generalized wavefront algorithm generates smooth and safe paths around obstacles that meet the required kinematic conditions associated with the actual maneuverability of mobile robots and significantly reduces the planned path length compared with the results obtained with the A∗ algorithm and the optimized RRT algorithm with a computation time acceptable for real-time applications. Therefore, the generated path is not only smooth and effective but also conforms to actual robot maneuverability in practical applications.

The Study on Mobile Robot Path Planning Based on Frog Leaping Algorithm

2012 ◽  
Vol 490-495 ◽  
pp. 808-812
Author(s):  
Zheng Ran Zhang ◽  
Ji Ying Yin
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimization Problem ◽  
Optimal Path ◽  
Robot Path Planning ◽  
Unknown Environment ◽  
Simulation Results ◽  
Robot Path

We have proposed a method of robot path planning in a partially unknown environment in this paper. We regard the problem of robot path planning as an optimization problem and solve it with the SFL algorithm. The position of globally best frog in each iterative is selected, and reached by the robot in sequence. The obstacles are detected by the robot sensors are applied to update the information of the environment. The optimal path is generated until the robot reaches its target. The simulation results validate the feasibility of the proposed method.

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