scholarly journals Path Planning for Mobile Robot Based on Improved Bat Algorithm

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4389
Author(s):  
Xin Yuan ◽  
Xinwei Yuan ◽  
Xiaohu Wang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimal Solution ◽  
Weighted Graph ◽  
Bat Algorithm ◽  
Planning Methods ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Window Approach ◽  
Switch Strategy

Bat algorithm has disadvantages of slow convergence rate, low convergence precision and weak stability. In this paper, we designed an improved bat algorithm with a logarithmic decreasing strategy and Cauchy disturbance. In order to meet the requirements of global optimal and dynamic obstacle avoidance in path planning for a mobile robot, we combined bat algorithm (BA) and dynamic window approach (DWA). An undirected weighted graph is constructed by setting virtual points, which provide path switch strategies for the robot. The simulation results show that the improved bat algorithm is better than the particle swarm optimization algorithm (PSO) and basic bat algorithm in terms of the optimal solution. Hybrid path planning methods can significantly reduce the path length compared with the dynamic window approach. Path switch strategy is proved effective in our simulations.

Delaunay Graph Based Path Planning of Dynamic Obstacle Avoidance Method for Mobile

2011 ◽  
Vol 217-218 ◽  
pp. 1775-1780
Author(s):  
Hui Ying Dong ◽  
Yang Song ◽  
Yu Zhao
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Working Space ◽  
Optimum Path ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Approximate Shortest Path

This paper is about dynamic obstacle avoidance. Delaunay Graph is used for modeling the working space, an approximate shortest path of mobile robot is determined by using floyd algorithm. Path can be found easily with genetic algorithm. Then genetic algorithm is used for obtaining the optimum path. It may meet which dynamic obstacle when robot follows optimum path. so it should avoid it. Results of simulation show that this path planning method is simple and realized easily.

scholarly journals An Effective Dynamic Path Planning Approach for Mobile Robots Based on Ant Colony Fusion Dynamic Windows

Machines ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 50
Author(s):  
Liwei Yang ◽  
Lixia Fu ◽  
Ping Li ◽  
Jianlin Mao ◽  
Ning Guo
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Dynamic Environment ◽  
Dynamic Environments ◽  
Ant Colony ◽  
Complex Dynamic ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Window Approach ◽  
Search Capability

To further improve the path planning of the mobile robot in complex dynamic environments, this paper proposes an enhanced hybrid algorithm by considering the excellent search capability of the ant colony optimization (ACO) for global paths and the advantages of the dynamic window approach (DWA) for local obstacle avoidance. Firstly, we establish a new dynamic environment model based on the motion characteristics of the obstacles. Secondly, we improve the traditional ACO from the pheromone update and heuristic function and then design a strategy to solve the deadlock problem. Considering the actual path requirements of the robot, a new path smoothing method is present. Finally, the robot modeled by DWA obtains navigation information from the global path, and we enhance its trajectory tracking capability and dynamic obstacle avoidance capability by improving the evaluation function. The simulation and experimental results show that our algorithm improves the robot's navigation capability, search capability, and dynamic obstacle avoidance capability in unknown and complex dynamic environments.

A Review of Path Planning Method for Mobile Robot

2014 ◽  
Vol 1030-1032 ◽  
pp. 1588-1591 ◽  
Author(s):  
Zong Sheng Wu ◽  
Wei Ping Fu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimal Path ◽  
Grid Method ◽  
Field Method ◽  
Planning Method ◽  
Artificial Potential Field ◽  
Planning Methods ◽  
Basic Ideas ◽  
Artificial Potential Field Method

The ability of a mobile robot to plan its path is the key task in the field of robotics, which is to find a shortest, collision free, optimal path in the various scenes. In this paper, different existing path planning methods are presented, and classified as: geometric construction method, artificial intelligent path planning method, grid method, and artificial potential field method. This paper briefly introduces the basic ideas of the four methods and compares them. Some challenging topics are presented based on the reviewed papers.

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