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.

Simulation research for mobile robot path planning based on improved artificial potential field method recommended by the AsiaSim

2017 ◽  
Vol 08 (02) ◽  
pp. 1750046 ◽  
Author(s):  
Pengqi Hou ◽  
Hu Pan ◽  
Chen Guo
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Potential Field ◽  
Field Method ◽  
Repulsive Force ◽  
Artificial Potential Field ◽  
Target Point ◽  
Robot Path Planning ◽  
Simulation Research ◽  
Robot Path

Mobile robot path planning is an important research branch in the field of mobile robots. The main disadvantage of the traditional artificial potential field (APF) method is prone to local minima problems. Improved artificial potential field (IAPF) method is presented in this paper to solve the problem in the traditional APF method for robot path planning in different conditions. We introduce the distance between the robot and the target point to the function of the original repulsive force field and change the original direction of the repulsive force to avoid the trap problem caused by the local minimum point. The IAPF method is suitable for mobile robot path planning in the complicated environment. Simulation and experiment results at the robot platform illustrated the superiority of the modified IAPF method.

Intelligent Agent Integration of On-Board and Off-Board Sensors Systems for Mobile Robot Path Planning

2011 ◽  
Vol 403-408 ◽  
pp. 4893-4900
Author(s):  
Fayeq Kamal ◽  
Keith Brown ◽  
Nick Taylor
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Initial Position ◽  
Target Point ◽  
Indoor Environments ◽  
Robot Path Planning ◽  
Novel Approach ◽  
Robot Path

The paper describes a novel approach of using distributed intelligent agents for the integration on-board and off-board sensors for mobile robot path planning in indoor environments. The system gives the robot a prior knowledge about the path state, which will be taken by the robot during navigating from an initial position to a target point. This enables the robot to intelligently decide in advance which path should be taken before reaching a point where a barrier to progress may have appeared. The system takes advantage of surveillance cameras already in buildings to aid the robot to plan a path. We have built intelligent agent based system that supports controlling the robot efficiently, using cameras available in the building and managing the communication between agents. The multi-agent system architecture includes two platforms, each platform consist of different agents connected together wirelessly using a JADE middleware platform.

scholarly journals Path planning for mobile robot using an enhanced ant colony optimization and path geometric optimization

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110192
Author(s):  
Songcan Zhang ◽  
Jiexin Pu ◽  
Yanna Si ◽  
Lifan Sun
Keyword(s):  
Path Planning ◽  
Convergence Rate ◽  
Mobile Robot ◽  
Local Optimization ◽  
Ant Colony ◽  
Ant Colony System ◽  
Geometric Features ◽  
Robot Path Planning ◽  
Computation Efficiency ◽  
Robot Path

Path planning of mobile robots in complex environments is the most challenging research. A hybrid approach combining the enhanced ant colony system with the local optimization algorithm based on path geometric features, called EACSPGO, has been presented in this study for mobile robot path planning. Firstly, the simplified model of pheromone diffusion, the pheromone initialization strategy of unequal allocation, and the adaptive pheromone update mechanism have been simultaneously introduced to enhance the classical ant colony algorithm, thus providing a significant improvement in the computation efficiency and the quality of the solutions. A local optimization method based on path geometric features has been designed to further optimize the initial path and achieve a good convergence rate. Finally, the performance and advantages of the proposed approach have been verified by a series of tests in the mobile robot path planning. The simulation results demonstrate that the presented EACSPGO approach provides better solutions, adaptability, stability, and faster convergence rate compared to the other tested optimization algorithms.

Sign in / Sign up

Export Citation Format

Share Document