多策略增强的秘书鸟优化算法用于机器人臂的高精度反向动力学
Xuhao Chen1, Nuohan Lin2, Fan Zhang3
1Southwest University, College of Engineering and Technology, Chongqing, China.
PloS one
|August 29, 2025
概括
这项研究引入了一种改进的优化算法 (ISBOA),用于精确的机器人手臂控制烟火式粮食组装. 在复杂的组装任务中,ISBOA提高了准确性和稳定性.
科学领域:
- 机器人技术
- 控制系统
- 优化算法
背景情况:
- 需要高精度的机器人手臂运动控制.
- 反向动力学对于机器人手臂轨迹的规划至关重要.
- 现有的算法面临着局部优化和多DOF机器人臂的缓慢融合等挑战.
研究的目的:
- 开发一个高精度的机器人臂反向运动模型.
- 改进秘书鸟优化算法 (SBOA) 的反向动力学性能.
- 在烟火组装中验证改进算法的有效性.
主要方法:
- 重构逆动力学作为一个受约束的优化问题.
- 开发了一种多策略改进的秘书鸟优化算法 (ISBOA),包括对立变异扰动,金弦发展和进化策略.
- 在4,6和7-DOF机器人手臂上进行模拟实验.
- 使用PCA缩小维度和K-平均集群进行结果分析.
- 实施了MATLAB-CoppeliaSim-UR16e实验平台,用于现实世界的验证.
主要成果:
- 与SBOA相比,ISBOA在解决反动力学问题方面表现出更好的表现.
- 数字实验证实了ISBOA的有效性并提高了解决方案的多样性.
- 对比分析显示ISBOA在组装精度,单一位置处理和成功率方面的优势超过分析和牛顿代方法.
- ISBOA在烟火加工中取得了更高的抓取和组装成功率.
结论:
- 拟议的ISBOA对于高精度的机器人手臂控制在烟火加工中非常有效.
- 与传统方法相比,ISBOA具有显著的优势,特别是在处理复杂的组装任务时.
- 开发的算法显示了需要精确机器人操作的实用工程应用的强大潜力.
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