一个基于自适应边缘检测和FSPS-BIT*路径规划的内空白机器人的框架
Rui Tang1, Shirong Guo2, Kunfu Wang1
1College of Advanced Manufacturing, Fuzhou University, Jinjiang, 362200, China.
Scientific reports
|September 9, 2024
概括
这项研究介绍了一种适应性机器人系统用于内空白,提高制造中的精度. 该系统使用先进的边缘检测和路径规划,在各种照明条件下准确地处理工件.
科学领域:
- 机器人和自动化机器人与自动化
- 制造业 工程 制造工程
- 计算机视觉 计算机视觉
背景情况:
- 传统的内空白系统需要精确的工件定位和辅助设备,限制了灵活性.
- 现有的机器人系统在制造过程中面临着适应不同照明条件的挑战.
研究的目的:
- 开发一个适应性机器人系统用于内空白,克服当前模型的局限性.
- 通过智能自动化提高内生产的精度和灵活性.
主要方法:
- 一个自适应的空白机器人系统,集成一个工业机器人臂,RGB-D摄像头和一个定制的空白桌.
- 一个边缘检测框架使用颜色特征和形态参数通过粒子群优化 (PSO) 优化.
- 一个路径规划框架 (FSPS-BIT*),结合FSPS和BIT*算法,以实现高效的机器人手臂运动.
主要成果:
- 在不同的照明条件下,成功地适应内边缘轮的识别.
- 在空白过程中为机器人手臂进行高效和精确的路径规划.
- 综合机器人系统的可行性证明,用于灵活的内生产.
结论:
- 拟议的自适应式机器人系统通过消除精确预定位的需要,显著改善了内空白生产.
- 创新的边缘检测和路径规划框架可以在可变照明下进行稳健的操作,提高制造效率.
- 这项技术为当代机械加工和制造业提供了灵活而精确的解决方案.
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