scholarly journals Modular Robotic Design and Reconfiguring Path Planning

2022 ◽  
Vol 12 (2) ◽  
pp. 723
Author(s):  
Ye Dai ◽  
Chao-Fang Xiang ◽  
Zhao-Xu Liu ◽  
Zhao-Long Li ◽  
Wen-Yin Qu ◽  
...  
Keyword(s):  
Path Planning ◽  
Industrial Application ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Configuration Design ◽  
Functional Modules ◽  
Simulation Experiments ◽  
Innovative Design ◽  
And Performance ◽  
Robot Configurations

The modular robot is becoming a prevalent research object in robots because of its unique configuration advantages and performance characteristics. It is possible to form robot configurations with different functions by reconfiguring functional modules. This paper focuses on studying the modular robot’s configuration design and self-reconfiguration process and hopes to realize the industrial application of the modular self-reconfiguration robot to a certain extent. We design robotic configurations with different DOF based on the cellular module of the hexahedron and perform the kinematic analysis of the structure. An innovative design of a modular reconfiguration platform for conformational reorganization is presented, and the collaborative path planning between different modules in the reconfiguration platform is investigated. We propose an optimized ant colony algorithm for reconfiguration path planning and verify the superiority and rationality of this algorithm compared with the traditional ant colony algorithm for platform path planning through simulation experiments.

Path Planning for the Chassis of Duct-Cleaning Robot Based on Ant Colony Algorithm

2012 ◽  
Vol 190-191 ◽  
pp. 715-718
Author(s):  
Qian Zhu ◽  
Wei Sun ◽  
Zhi Wei Zhou ◽  
Su Wei Zhang
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Optimal Path ◽  
Grid Method ◽  
Ant Colony ◽  
Simulation Experiments ◽  
Environment Model ◽  
Cleaning Robot ◽  
Duct Cleaning Robot ◽  
Duct Cleaning

For the path planning for the chassis of duct cleaning robot in an obstacle environment, ant colony algorithm and grid method are adopted to achieve an optimal path between two different arbitrary points and establish the environment model. The results of computer simulation experiments demonstrate the effectiveness of ant colony algorithm applied in path planning for the chassis of duct cleaning robot.

scholarly journals Path Planning Based on an Improved Ant Colony Algorithm

2018 ◽  
Vol 228 ◽  
pp. 01010
Author(s):  
Miaomiao Wang ◽  
Zhenglin Li ◽  
Qing Zhao ◽  
Fuyuan Si ◽  
Dianfang Huang
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Search Algorithm ◽  
Convergence Speed ◽  
Ant Colony ◽  
Local Optimum ◽  
Pheromone Concentration ◽  
Suppression Strategy ◽  
Improved Ant Colony Algorithm ◽  
Robot Path

The classical ant colony algorithm has the disadvantages of initial search blindness, slow convergence speed and easy to fall into local optimum when applied to mobile robot path planning. This paper presents an improved ant colony algorithm in order to solve these disadvantages. First, the algorithm use A* search algorithm for initial search to generate uneven initial pheromone distribution to solve the initial search blindness problem. At the same time, the algorithm also limits the pheromone concentration to avoid local optimum. Then, the algorithm optimizes the transfer probability and adopts the pheromone update rule of "incentive and suppression strategy" to accelerate the convergence speed. Finally, the algorithm builds an adaptive model of pheromone coefficient to make the pheromone coefficient adjustment self-adaptive to avoid falling into a local minimum. The results proved that the proposed algorithm is practical and effective.

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