智能脱冰机器人的目标定位方法基于非线性自动干扰排斥神经网络
1College of Modern Science and Technology, China Jiliang University, Hangzhou, 310018, Zhejiang, China.
Heliyon
|May 6, 2024
概括
本研究介绍了用于脱冰机器人的视觉导航系统,提高了复杂环境中的实时性能和准确性. 这种新方法可以为机器人提供更快,更精确的导航和任务执行.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 计算机视觉 计算机视觉
- 人工智能的人工智能
背景情况:
- 传统的同时定位和映射 (SLAM) 系统面临的挑战是多次代,长时间的计算时间,以及脱冰机器人的实时性能差.
- 现有的系统在与非线性优化作斗争,阻碍了在动态环境中的高效导航.
研究的目的:
- 为间歇性行走脱冰机器人设计和实施有效的视觉导航方案.
- 通过提高实时性能和准确性来克服现有的SLAM系统的局限性.
- 开发一个强大的视觉伺服控制方案,用于机器人任务操作,未知系统校准和目标深度.
主要方法:
- 设计了一种视觉导航系统,包括计算机图像采集单元,图像处理模块和视觉导航参数提取算法.
- 实施了用于机器人任务操作的视觉伺服控制方案.
- 通过机器人视觉系统校准,实现了摄像头像素坐标和机器人基地坐标之间的坐标转换.
主要成果:
- 拟议的方法可以在模拟和实验中快速准确地识别异常点云.
- 实现了每秒53.65的高传输率.
- 证明了最大的空间定位精度误差为10.6毫米,机器人端效应器运动稳定,抓取精度高.
结论:
- 开发的视觉导航系统满足了除冰机器人的导航要求,提供了更好的速度和精度.
- 视觉伺服控制方案确保了机器人的稳定和准确的运动,这对于抓取和定位等复杂任务至关重要.
- 这种方法提高了脱冰机器人的实时性能和准确性,使它们在操作环境中更有效.
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