scholarly journals Improved Ant Colony Algorithm-based Automated Guided Vehicle Path Planning Research for Sensor-aware Obstacle Avoidance

2021 ◽  
Vol 33 (8) ◽  
pp. 2679
Author(s):  
Rong Liu
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Automated Guided Vehicle ◽  
Vehicle Path ◽  
Improved Ant Colony Algorithm

Obstacle Avoidance Path Planning for Harvesting Robot Manipulator Based on MAKLINK Graph and Improved Ant Colony Algorithm

2014 ◽  
Vol 530-531 ◽  
pp. 1063-1067 ◽  
Author(s):  
Wei Ji ◽  
Jun Le Li ◽  
De An Zhao ◽  
Yang Jun
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Ant Colony Algorithm ◽  
Robot Manipulator ◽  
Ant Colony ◽  
Dijkstra Algorithm ◽  
Short Time ◽  
Vector Description ◽  
Harvesting Robot ◽  
Improved Ant Colony Algorithm

To the problems of real-time obstacle avoidance path planning for apple harvesting robot manipulator in dynamic and unstructured environment, a method based on improved ant colony algorithm is presented. Firstly, Vector description is utilized to describe the area where obstacles such as branches is located as irregular polygon in free space, and MAKLINK graph is used to build up the environment space model. Then, the improved Dijkstra algorithm is used to find the initial walk path for apple harvesting robot manipulator. Finally, the improved ant colony algorithm is applied to optimize the initial path. The experiment result shows that the proposed method is simple and the robot manipulator can avoid the branches to pick the apple successfully in a relatively short time.

scholarly journals An Improved Ant Colony Algorithm of Robot Path Planning for Obstacle Avoidance

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Hong-Jun Wang ◽  
Yong Fu ◽  
Zhuo-Qun Zhao ◽  
You-Jun Yue
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Robot Control ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Ant Colony Algorithms ◽  
Mobile Robot Control ◽  
Technical Issues ◽  
Improved Ant Colony Algorithm ◽  
Robot Path

The obstacle avoidance in path planning, a hot topic in mobile robot control, has been extensively investigated. The existing ant colony algorithms, however, remain as drawbacks including failing to cope with narrow aisles in working areas, large amount of calculation, etc. To address above technical issues, an improved ant colony algorithm is proposed for path planning. In this paper, a new weighted adjacency matrix is presented to determine the walking direction and the narrow aisles therefore are avoided by redesigning the walking rules. Also, the best ant and the worst ant are introduced for the adjustment of pheromone to facilitate the searching process. The proposed algorithm guarantees that robots are able to find a satisfying path in the presence of narrow aisles. The simulation results show the effectiveness of the proposed algorithm.

Cross-country path planning based on improved ant colony algorithm

2013 ◽  
Vol 33 (4) ◽  
pp. 1157-1160
Author(s):  
Tianyi WU ◽  
Jiheng XU ◽  
Jianyong LIU
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Cross Country ◽  
Improved Ant Colony Algorithm
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