Investigation into the Efficient Cooperative Planning Approach for Dual-Arm Picking Sequences of Dwarf, High-Density Safflowers
Path planning for picking safflowers is a key component in ensuring the efficient operation of robotic safflower-picking systems. However, existing single-arm picking devices have become a bottleneck due to their limited operating range, and a breakthrough in multi-arm cooperative picking is urgentl...
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MDPI AG
2025-07-01
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| author | Zhenguo Zhang Peng Xu Binbin Xie Yunze Wang Ruimeng Shi Junye Li Wenjie Cao Wenqiang Chu Chao Zeng |
| author_facet | Zhenguo Zhang Peng Xu Binbin Xie Yunze Wang Ruimeng Shi Junye Li Wenjie Cao Wenqiang Chu Chao Zeng |
| author_sort | Zhenguo Zhang |
| collection | DOAJ |
| description | Path planning for picking safflowers is a key component in ensuring the efficient operation of robotic safflower-picking systems. However, existing single-arm picking devices have become a bottleneck due to their limited operating range, and a breakthrough in multi-arm cooperative picking is urgently needed. To address the issue of inadequate adaptability in current path planning strategies for dual-arm systems, this paper proposes a novel path planning method for dual-arm picking (LTSACO). The technique centers on a dynamic-weight heuristic strategy and achieves optimization through the following steps: first, the K-means clustering algorithm divides the target area; second, the heuristic mechanism of the Ant Colony Optimization (ACO) algorithm is improved by dynamically adjusting the weight factor of the state transition probability, thereby enhancing the diversity of path selection; third, a 2-OPT local search strategy eliminates path crossings through neighborhood search; finally, a cubic Bézier curve heuristically smooths and optimizes the picking trajectory, ensuring the continuity of the trajectory’s curvature. Experimental results show that the length of the parallelogram trajectory, after smoothing with the Bézier curve, is reduced by 20.52% compared to the gantry trajectory. In terms of average picking time, the LTSACO algorithm reduces the time by 2.00%, 2.60%, and 5.60% compared to DCACO, IACO, and the traditional ACO algorithm, respectively. In conclusion, the LTSACO algorithm demonstrates high efficiency and strong robustness, providing an effective optimization solution for multi-arm cooperative picking and significantly contributing to the advancement of multi-arm robotic picking systems. |
| format | Article |
| id | doaj-art-b5637af90bb442fcb3b915af033498df |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-b5637af90bb442fcb3b915af033498df2025-08-20T02:47:17ZengMDPI AGSensors1424-82202025-07-012514445910.3390/s25144459Investigation into the Efficient Cooperative Planning Approach for Dual-Arm Picking Sequences of Dwarf, High-Density SafflowersZhenguo Zhang0Peng Xu1Binbin Xie2Yunze Wang3Ruimeng Shi4Junye Li5Wenjie Cao6Wenqiang Chu7Chao Zeng8College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaPath planning for picking safflowers is a key component in ensuring the efficient operation of robotic safflower-picking systems. However, existing single-arm picking devices have become a bottleneck due to their limited operating range, and a breakthrough in multi-arm cooperative picking is urgently needed. To address the issue of inadequate adaptability in current path planning strategies for dual-arm systems, this paper proposes a novel path planning method for dual-arm picking (LTSACO). The technique centers on a dynamic-weight heuristic strategy and achieves optimization through the following steps: first, the K-means clustering algorithm divides the target area; second, the heuristic mechanism of the Ant Colony Optimization (ACO) algorithm is improved by dynamically adjusting the weight factor of the state transition probability, thereby enhancing the diversity of path selection; third, a 2-OPT local search strategy eliminates path crossings through neighborhood search; finally, a cubic Bézier curve heuristically smooths and optimizes the picking trajectory, ensuring the continuity of the trajectory’s curvature. Experimental results show that the length of the parallelogram trajectory, after smoothing with the Bézier curve, is reduced by 20.52% compared to the gantry trajectory. In terms of average picking time, the LTSACO algorithm reduces the time by 2.00%, 2.60%, and 5.60% compared to DCACO, IACO, and the traditional ACO algorithm, respectively. In conclusion, the LTSACO algorithm demonstrates high efficiency and strong robustness, providing an effective optimization solution for multi-arm cooperative picking and significantly contributing to the advancement of multi-arm robotic picking systems.https://www.mdpi.com/1424-8220/25/14/4459picking robotdual-arm collaborationant colony optimizationpath planningpicking trajectory |
| spellingShingle | Zhenguo Zhang Peng Xu Binbin Xie Yunze Wang Ruimeng Shi Junye Li Wenjie Cao Wenqiang Chu Chao Zeng Investigation into the Efficient Cooperative Planning Approach for Dual-Arm Picking Sequences of Dwarf, High-Density Safflowers Sensors picking robot dual-arm collaboration ant colony optimization path planning picking trajectory |
| title | Investigation into the Efficient Cooperative Planning Approach for Dual-Arm Picking Sequences of Dwarf, High-Density Safflowers |
| title_full | Investigation into the Efficient Cooperative Planning Approach for Dual-Arm Picking Sequences of Dwarf, High-Density Safflowers |
| title_fullStr | Investigation into the Efficient Cooperative Planning Approach for Dual-Arm Picking Sequences of Dwarf, High-Density Safflowers |
| title_full_unstemmed | Investigation into the Efficient Cooperative Planning Approach for Dual-Arm Picking Sequences of Dwarf, High-Density Safflowers |
| title_short | Investigation into the Efficient Cooperative Planning Approach for Dual-Arm Picking Sequences of Dwarf, High-Density Safflowers |
| title_sort | investigation into the efficient cooperative planning approach for dual arm picking sequences of dwarf high density safflowers |
| topic | picking robot dual-arm collaboration ant colony optimization path planning picking trajectory |
| url | https://www.mdpi.com/1424-8220/25/14/4459 |
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