Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm
Assembly robots have become the core equipment of high-precision flexible automatic assembly systems with a small working range. Among different fields of robot technology, path planning is one of the most important branches. In the present study, an elite smoothing ant colony algorithm (ESACO) is p...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-09-01
|
| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/14/9/1843 |
| _version_ | 1797481994423107584 |
|---|---|
| author | Xiaoling Meng Xijing Zhu |
| author_facet | Xiaoling Meng Xijing Zhu |
| author_sort | Xiaoling Meng |
| collection | DOAJ |
| description | Assembly robots have become the core equipment of high-precision flexible automatic assembly systems with a small working range. Among different fields of robot technology, path planning is one of the most important branches. In the present study, an elite smoothing ant colony algorithm (ESACO) is proposed for spatial obstacle avoidance path planning of the grasping manipulator. In this regard, the state transition probability and pheromone update strategies are improved to enhance the search capability of path planning symmetry and the convergence of the algorithm. Then a segmented B-spline curve is presented to eliminate path folding points and generate a smooth path. Finally, a manipulator control system based on the Arduino Uno microcontroller is designed to drive the manipulator according to the planned trajectory. The experimental results show that the performance of the ESACO algorithm in different scenarios has symmetry advantages, and the manipulator can efficiently complete the simulation trajectory with high accuracy. The proposed algorithm provides a feasible scheme for the efficient planning of manipulators in equipment manufacturing workshops. |
| first_indexed | 2024-03-09T22:22:00Z |
| format | Article |
| id | doaj.art-3c170b807a674acbb02dde7678c33148 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-09T22:22:00Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-3c170b807a674acbb02dde7678c331482023-11-23T19:11:52ZengMDPI AGSymmetry2073-89942022-09-01149184310.3390/sym14091843Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony AlgorithmXiaoling Meng0Xijing Zhu1Shanxi Key Laboratory of Advanced Manufacturing Technology, North University of China, Taiyuan 030051, ChinaShanxi Key Laboratory of Advanced Manufacturing Technology, North University of China, Taiyuan 030051, ChinaAssembly robots have become the core equipment of high-precision flexible automatic assembly systems with a small working range. Among different fields of robot technology, path planning is one of the most important branches. In the present study, an elite smoothing ant colony algorithm (ESACO) is proposed for spatial obstacle avoidance path planning of the grasping manipulator. In this regard, the state transition probability and pheromone update strategies are improved to enhance the search capability of path planning symmetry and the convergence of the algorithm. Then a segmented B-spline curve is presented to eliminate path folding points and generate a smooth path. Finally, a manipulator control system based on the Arduino Uno microcontroller is designed to drive the manipulator according to the planned trajectory. The experimental results show that the performance of the ESACO algorithm in different scenarios has symmetry advantages, and the manipulator can efficiently complete the simulation trajectory with high accuracy. The proposed algorithm provides a feasible scheme for the efficient planning of manipulators in equipment manufacturing workshops.https://www.mdpi.com/2073-8994/14/9/1843elite smoothing ant colony algorithmgrasping manipulatorautonomous obstacle avoidanceglobal path planning |
| spellingShingle | Xiaoling Meng Xijing Zhu Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm Symmetry elite smoothing ant colony algorithm grasping manipulator autonomous obstacle avoidance global path planning |
| title | Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm |
| title_full | Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm |
| title_fullStr | Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm |
| title_full_unstemmed | Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm |
| title_short | Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm |
| title_sort | autonomous obstacle avoidance path planning for grasping manipulator based on elite smoothing ant colony algorithm |
| topic | elite smoothing ant colony algorithm grasping manipulator autonomous obstacle avoidance global path planning |
| url | https://www.mdpi.com/2073-8994/14/9/1843 |
| work_keys_str_mv | AT xiaolingmeng autonomousobstacleavoidancepathplanningforgraspingmanipulatorbasedonelitesmoothingantcolonyalgorithm AT xijingzhu autonomousobstacleavoidancepathplanningforgraspingmanipulatorbasedonelitesmoothingantcolonyalgorithm |