scholarly journals Solving the Path Planning Problem in Mobile Robotics with the Multi-Objective Evolutionary Algorithm

2018 ◽  
Vol 8 (9) ◽  
pp. 1425 ◽  
Author(s):  
Yang Xue ◽  
Jian-Qiao Sun
Keyword(s):  
Path Planning ◽  
Evolutionary Algorithm ◽  
Mobile Robotics ◽  
Good Choice ◽  
Target Point ◽  
Planning Problem ◽  
Multi Objective ◽  
Starting Point ◽  
Feasible Path ◽  
Path Planning Problem

Path planning problems involve finding a feasible path from the starting point to the target point. In mobile robotics, path planning (PP) is one of the most researched subjects at present. Since the path planning problem is an NP-hard problem, it can be solved by multi-objective evolutionary algorithms (MOEAs). In this article, we propose a multi-objective method for solving the path planning problem. It is a population evolutionary algorithm and solves three different objectives (path length, safety, and smoothness) to acquire precise and effective solutions. In addition, five scenarios and another existing method are used to test the proposed algorithm. The results show the advantages of the algorithm. In particular, different quality metrics are used to assess the obtained results. In the end, the research indicates that the proposed multi-objective evolutionary algorithm is a good choice for solving the path planning problem.

Solving the multi-objective path planning problem in mobile robotics with a firefly-based approach

2015 ◽  
Vol 21 (4) ◽  
pp. 949-964 ◽  
Author(s):  
Alejandro Hidalgo-Paniagua ◽  
Miguel A. Vega-Rodríguez ◽  
Joaquín Ferruz ◽  
Nieves Pavón
Keyword(s):  
Path Planning ◽  
Mobile Robotics ◽  
Planning Problem ◽  
Multi Objective ◽  
Path Planning Problem

Path Planning for Spheres in Three Dimensional Environments With Low Interference Index

1994 ◽  
Author(s):  
Duane W. Storti ◽  
Debasish Dutta
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Configuration Space ◽  
Local Knowledge ◽  
Three Dimensional ◽  
Target Point ◽  
Planning Problem ◽  
Spherical Object ◽  
Starting Point ◽  
Path Planning Problem

Abstract We consider the path planning problem for a spherical object moving through a three-dimensional environment composed of spherical obstacles. Given a starting point and a terminal or target point, we wish to determine a collision free path from start to target for the moving sphere. We define an interference index to count the number of configuration space obstacles whose surfaces interfere simultaneously. In this paper, we present algorithms for navigating the sphere when the interference index is ≤ 2. While a global calculation is necessary to characterize the environment as a whole, only local knowledge is needed for path construction.

Multi Objective Path Finding Based on Adding-Weight A* Algorithm

2014 ◽  
Vol 1079-1080 ◽  
pp. 711-715 ◽  
Author(s):  
Qiang Wang ◽  
Guan Cheng Wang ◽  
Fan Fei ◽  
Shuai Lü
Keyword(s):  
Path Planning ◽  
Operation Time ◽  
Planning Problem ◽  
Search Efficiency ◽  
A Algorithm ◽  
List Structure ◽  
Initial Node ◽  
Multi Objective ◽  
Linked List ◽  
Path Planning Problem

Multi-objective path planning is a path planning problem when there are more than one objective function to be optimized at the same time. This paper is based on traditional A* algorithm.To improve the algorithm A* and find out the shortest path in the different environments,we choose different weights and do global path planning by using improved evaluation function.We use the minimum binary heap in a linked list structure to manage the OPEN table,and the search efficiency has been improved.We compile the simulation program of path planning in the VC environment,then compare the operation time and generated paths by transforming the coordinates of the initial node and the goal node.Research shows that, the algorithm can improve the efficiency of the path planning efficiently.

scholarly journals An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Jiang Zhao ◽  
Dingding Cheng ◽  
Chongqing Hao
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Selection Strategy ◽  
Planning Problem ◽  
Evaporation Coefficient ◽  
Mobile Vehicle ◽  
Starting Point ◽  
Path Planning Problem ◽  
Improved Ant Colony Algorithm

This paper presents an improved ant colony algorithm for the path planning of the omnidirectional mobile vehicle. The purpose of the improved ant colony algorithm is to design an appropriate route to connect the starting point and ending point of the environment with obstacles. Ant colony algorithm, which is used to solve the path planning problem, is improved according to the characteristics of the omnidirectional mobile vehicle. And in the improved algorithm, the nonuniform distribution of the initial pheromone and the selection strategy with direction play a very positive role in the path search. The coverage and updating strategy of pheromone is introduced to avoid repeated search reducing the effect of the number of ants on the performance of the algorithm. In addition, the pheromone evaporation coefficient is segmented and adjusted, which can effectively balance the convergence speed and search ability. Finally, this paper provides a theoretical basis for the improved ant colony algorithm by strict mathematical derivation, and some numerical simulations are also given to illustrate the effectiveness of the theoretical results.

scholarly journals Mobile Robot Path Planning with a Non-Dominated Sorting Genetic Algorithm

2018 ◽  
Vol 8 (11) ◽  
pp. 2253 ◽  
Author(s):  
Yang Xue
Keyword(s):  
Genetic Algorithm ◽  
Evolutionary Algorithms ◽  
Path Planning ◽  
Optimization Problems ◽  
Planning Problem ◽  
Nsga Ii ◽  
Multi Objective ◽  
Mutation Operators ◽  
Comparison Results ◽  
Path Planning Problem

In many areas, such as mobile robots, video games and driverless vehicles, path planning has always attracted researchers’ attention. In the field of mobile robotics, the path planning problem is to plan one or more viable paths to the target location from the starting position within a given obstacle space. Evolutionary algorithms can effectively solve this problem. The non-dominated sorting genetic algorithm (NSGA-II) is currently recognized as one of the evolutionary algorithms with robust optimization capabilities and has solved various optimization problems. In this paper, NSGA-II is adopted to solve multi-objective path planning problems. Three objectives are introduced. Besides the usual selection, crossover and mutation operators, some practical operators are applied. Moreover, the parameters involved in the algorithm are studied. Additionally, another evolutionary algorithm and quality metrics are employed for examination. Comparison results demonstrate that non-dominated solutions obtained by the algorithm have good characteristics. Subsequently, the path corresponding to the knee point of non-dominated solutions is shown. The path is shorter, safer and smoother. This path can be adopted in the later decision-making process. Finally, the above research shows that the revised algorithm can effectively solve the multi-objective path planning problem in static environments.

Online cooperative path planning for multi-quadrotors in an unknown dynamic environment

2021 ◽  
pp. 095441002110166
Author(s):  
Zhenyue Jia ◽  
Ping Lin ◽  
Jiaolong Liu ◽  
Luyang Liang
Keyword(s):  
Path Planning ◽  
Partial Information ◽  
Three Dimensional ◽  
Dynamic Environment ◽  
Planning Problem ◽  
Planning Strategy ◽  
Coordination Strategy ◽  
Planning Strategies ◽  
Feasible Path ◽  
Path Planning Problem

The online cooperative path planning problem is discussed for multi-quadrotor maneuvering in an unknown dynamic environment. Based on the related basic concepts, typical three-dimensional obstacle models, such as spherical and cubic, and their collision checking criteria are presented in this article. An improved rapidly exploring random tree (RRT) algorithm with goal bias and greed property is proposed based on the heuristic search strategy to overcome the shortcomings of the classical RRT algorithm. Not only are the kinematic constraints of the quadrotor established but the time and space coordination strategy matching with the improved RRT algorithm is also presented in this article. Furthermore, a novel online collision avoidance strategy according to the partial information of the surrounding environment is proposed. On the basis of the above work, a distributed online path planning strategy is proposed to obtain the feasible path for each quadrotor. Numerical simulation results show that the improved RRT algorithm has better search efficiency than the classical RRT algorithm. And the satisfactory path planning and path tracking results prove that the above model and related planning strategies are reasonable and effective.

scholarly journals Bypassing or flying above the obstacles? A novel multi-objective UAV path planning problem

2020 ◽  
Author(s):  
Mahmoud Golabi ◽  
Soheila Ghambari ◽  
Julien Lepagnot ◽  
Laetitia Jourdan ◽  
Mathieu Brevilliers ◽  
...  
Keyword(s):  
Path Planning ◽  
Planning Problem ◽  
Multi Objective ◽  
Path Planning Problem
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