煤矸石智能分拣机器人研究进展与关键技术

张烨; 马宏伟; 王鹏; 曹现刚; 魏小荣; 周文剑

doi:10.13272/j.issn.1671-251x.2022100048

煤矸石智能分拣机器人研究进展与关键技术

doi: 10.13272/j.issn.1671-251x.2022100048

张烨^{1, 2,},
马宏伟^{1, 2},
王鹏^{1, 2},
曹现刚^{1, 2},
魏小荣^{1, 2},
周文剑^{1, 2}

1.
西安科技大学机械工程学院, 陕西西安　710054
2.
陕西省矿山机电装备智能检测与控制重点实验室, 陕西西安　710054

基金项目: 国家自然科学基金面上项目（51975468）

详细信息

作者简介:
张烨（1990—），女，陕西兴平人，工程师，博士研究生，主要从事机器视觉及机器人智能控制方面的研究工作，E-mail：xust-zy@xust.edu.cn

中图分类号: TD67
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出版历程
- 收稿日期: 2022-10-18
- 修回日期: 2022-11-28
- 网络出版日期: 2022-11-28

Research progress and key technologies of intelligent coal-gangue sorting robot

ZHANG Ye^{1, 2
,},
MA Hongwei^{1, 2},
WANG Peng^{1, 2},
CAO Xiangang^{1, 2},
WEI Xiaorong^{1, 2},
ZHOU Wenjian^{1, 2}

1.
College of Mechanical Engineering, Xi'an University of Science and Technology, Xi 'an 710054, China
2.
Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi'an 710054, China

摘要

摘要: 煤矿井下矸石被煤泥包裹，煤矸石识别难、分拣难；井下工作空间狭小，设备布局难、煤矸石分流难，因此，需要研发高性能、高可靠的煤矸石智能分拣机器人。分析了煤矸石智能分拣机器人中煤矸石识别、机器人轨迹规划、多动态目标多机器人协同控制技术的研究现状。指出煤矸石分拣工作环境复杂，其质量和形状不规则且呈随机分布，因此，复杂环境下煤矸石识别与抓取特征提取、非结构环境下煤矸石稳定可靠抓取、多目标任务多机器人智能协同分拣是煤矸石分拣智能机器人的3大关键技术，提出要实现机器人智能分拣煤矸石，还应在适应于井下的煤矸石识别与抓取特征提取、动态目标精确定位和同步跟踪、机械臂在线轨迹规划和多机械臂智能协同控制等方法上进行深入研究。通过对上述3大关键技术的梳理，总结得出：煤矸石数据集构建与扩增、煤矸石识别与抓取特征提取是实现煤矸石高效识别的关键技术；动态煤矸石精准跟踪、机械臂同步跟踪动态目标轨迹规划和快速大质量目标稳定抓取是实现机械臂稳定抓取煤矸石的关键技术；多任务高效分配、防碰撞路径规划和智能协同控制是实现多机械臂高效智能协同分拣的关键技术。针对目前存在的共性问题，提出了解决方案：在识别方面，研究基于多模态深度学习的煤矸石识别与抓取特征提取方法，实现井下煤矸石快速识别；在轨迹规划方面，研究动态煤矸石精准定位和实时跟踪方法，实现机器人对动态煤矸石的自适应稳定抓取；在协同分拣方面，构建多层多机械臂协同控制模型，实现多机械臂复杂环境下高效智能协同分拣。
- 煤矸石分拣 /
- 分拣机器人 /
- 煤矸石识别 /
- 机器人轨迹规划 /
- 智能协同分拣 /
- 稳定抓取
Abstract: The gangue is wrapped by slurry in underground coal mine, which causes difficult coal-gangue recognition and sorting. The underground working space is narrow, so the equipment layout is difficult, and the diversion of coal-gangue is difficult. Therefore, developing a high-performance, highly reliable intelligent coal-gangue sorting robot is necessary. The paper analyzes the research status of coal-gangue recognition, robot trajectory plan and multi-dynamic-target multi-robot collaborative control technology of intelligent coal-gangue sorting robot. This paper points out that the coal-gangue sorting work environment is complex, and its weight and shape of coal-gangue are irregular and randomly distributed. Therefore, the three key technologies for intelligent coal-gangue sorting robot are recognition and grasping features extraction of coal-gangue in complex environment, stable and reliable grasping of coal-gangue in unstructured environment, and intelligent collaborative sorting of multi-target multi-robot. It is proposed that in order to realize the intelligent sorting of coal-gangue by the robot, further research should be carried out. The research includes the methods of coal-gangue recognition and sorting feature extraction suitable for underground, accurate positioning and synchronous tracking of dynamic targets, online trajectory planning of mechanical arms, and intelligent collaborative control of multiple mechanical arms. By soring out the above three key technologies, it can be concluded as follows. The construction and expansion of coal-gangue data set, recognition and grasping features extraction of coal-gangue are the key technologies to achieve efficient coal-gangue recognition. Precise tracking of dynamic coal-gangue, trajectory planning of synchronous tracking dynamic target of mechanical arm and fast and stable grasping of large quality targets are the key technologies to realize stable coal-gangue grasping by mechanical arms. Multi-task efficient allocation, anti-collision path planning and intelligent collaborative control are the key technologies to achieve efficient intelligent collaborative sorting of multiple mechanical arms. According to the common problems at present, this paper puts forward the solutions. In the aspect of recognition, the method of coal-gangue recognition and grasping feature extraction based on multi-mode deep learning is studied to realize fast coal-gangue recognition suitable for the underground. In the aspect of trajectory planning, the precise positioning and real-time tracking methods of dynamic coal-gangue are studied to realize the adaptive and stable grasping of dynamic coal-gangue by the robot. In the aspect of collaborative sorting, a multi-layer multiple mechanical arms collaborative control model is built to achieve efficient intelligent collaborative sorting of multiple mechanical arms in the complex environment.
- coal-gangue sorting /
- sorting robot /
- coal-gangue recognition /
- robot trajectory planning /
- intelligent collaborative sorting /
- stable grasp

HTML全文

图 1 煤矸石智能分拣机器人

Figure 1. Intelligent coal-gangue sorting robot

下载: 全尺寸图片幻灯片

图 2 煤矸石识别与抓取特征提取方法

Figure 2. Recognition and grasping features extraction of coal-gangue

下载: 全尺寸图片幻灯片

图 3 机械臂动态目标精准跟踪与稳定抓取方法

Figure 3. Precise dynamic target tracking and stable grasping method of mechanical arm

下载: 全尺寸图片幻灯片

图 4 多机械臂复杂环境下高效智能协同分拣方法

Figure 4. Efficient and intelligent collaborative sorting method of multi-mechanical arm in complex environment

下载: 全尺寸图片幻灯片

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