scholarly journals A Mobile Service Robot Global Path Planning Method Based on Ant Colony Optimization and Fuzzy Control

2021 ◽  
Vol 11 (8) ◽  
pp. 3605
Author(s):  
Yong Tao ◽  
He Gao ◽  
Fan Ren ◽  
Chaoyong Chen ◽  
Tianmiao Wang ◽  
...  
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Ant Colony Optimization ◽  
Influence Factor ◽  
Convergence Speed ◽  
Ant Colony ◽  
Service Robot ◽  
Mobile Service ◽  
Global Path Planning ◽  
Mobile Service Robot

A global path planning method is proposed based on improved ant colony optimization according to the slow convergence speed in mobile service robot path planning. The distribution of initial pheromone is determined by the critical obstacle influence factor. The influence factor is introduced into the heuristic information to improve the convergence speed of the algorithm at an early stage. A new pheromone update rule is presented using fuzzy control to change the value of pheromone heuristic factor and expectation heuristic factor, adjusting the evaporation rate in stages. The method achieves fast convergence and guarantees global search capability. Finally, the simulation results show that the improved algorithm not only shortens the running time of global path planning, but also has a higher probability of obtaining a global optimal solution. The convergence speed of the algorithm is better than the traditional ant colony algorithm.

scholarly journals Mobile Robot Path Planning Based on Time Taboo Ant Colony Optimization in Dynamic Environment

2021 ◽  
Vol 15 ◽  
Author(s):  
Ni Xiong ◽  
Xinzhi Zhou ◽  
Xiuqing Yang ◽  
Yong Xiang ◽  
Junyong Ma
Keyword(s):  
Path Planning ◽  
Ant Colony Optimization ◽  
Dynamic Environment ◽  
Global Search ◽  
Convergence Speed ◽  
Ant Colony ◽  
Time Varying ◽  
Ant Colony Optimization Algorithm ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle

This article aims to improve the problem of slow convergence speed, poor global search ability, and unknown time-varying dynamic obstacles in the path planning of ant colony optimization in dynamic environment. An improved ant colony optimization algorithm using time taboo strategy is proposed, namely, time taboo ant colony optimization (TTACO), which uses adaptive initial pheromone distribution, rollback strategy, and pheromone preferential limited update to improve the algorithm's convergence speed and global search ability. For the poor global search ability of the algorithm and the unknown time-varying problem of dynamic obstacles in a dynamic environment, a time taboo strategy is first proposed, based on which a three-step arbitration method is put forward to improve its weakness in global search. For the unknown time-varying dynamic obstacles, an occupancy grid prediction model is proposed based on the time taboo strategy to solve the problem of dynamic obstacle avoidance. In order to improve the algorithm's calculation speed when avoiding obstacles, an ant colony information inheritance mechanism is established. Finally, the algorithm is used to conduct dynamic simulation experiments in a simulated factory environment and is compared with other similar algorithms. The experimental results show that the TTACO can obtain a better path and accelerate the convergence speed of the algorithm in a static environment and can successfully avoid dynamic obstacles in a dynamic environment.

Reflective Collision Avoidance for Mobile Service Robot in Person Coexistence Environment

2011 ◽  
Vol 23 (6) ◽  
pp. 999-1011 ◽  
Author(s):  
Takafumi Sonoura ◽  
◽  
Seiji Tokura ◽  
Tsuyoshi Tasaki ◽  
Fumio Ozaki ◽  
...  
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Retail Store ◽  
Autonomous Robot ◽  
Service Robot ◽  
Mobile Service ◽  
Simple Operation ◽  
Operation Rules ◽  
Mobile Service Robot

A person coexistence environment is always changing. For example, people in the environment move around, someone changes the arrangement of the furniture, and someone puts something on the floor. Tasks of a service robot to support people include many scenes that the robot should move around in this environment. Without sensing the objects in the environment, it is difficult for an autonomous robot to move in the person coexistence environment protecting a people’s safety. Thus, an advanced ability to avoid collisions by adapting to the environment is required for a robot. From the viewpoint of robustness, a reflective collision avoidance algorithm has been used with predefined map-based path planning. However, because the algorithm is composed of simple operation rules, a robot depending on the reflective collision avoidance algorithm may often moves inefficiently. To ensure efficient collision avoidance, we propose a reflective collision avoidance technique that corrects direction and magnitude of robot velocity independently using 1-dimensional potential-like functions ruled by a pseudo distance that modifies its own distance in proportion to an angle from the robot traveling direction to the obstacle direction. We verify the effectiveness of the proposed technique for a robot developed to serve persons in a retail store.

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