能源效率多机器人系统和消毒服务机器人在大型复杂环境中的开发
Chin-Sheng Chen1, Feng-Chieh Lin1, Chia-Jen Lin1,2
1Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 10608, Taiwan.
Sensors (Basel, Switzerland)
|July 8, 2023
概括
这项研究介绍了一种节能多机器人系统,该系统在长期运行期间将计算能耗降低54%. 该系统保持了高定位精度,这对于复杂环境中的服务机器人至关重要.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 人工智能的人工智能
- 计算机视觉 计算机视觉
背景情况:
- 带有图形计算的服务机器人越来越多地被使用,但长期的视觉同步定位和映射 (VSLAM) 会降低能源效率.
- 在动态人群和障碍物的大型环境中,局部化故障仍然存在,影响机器人的可靠性.
- 现有的多机器人系统在能源管理和强大的本地化方面面临着长期运营的挑战.
研究的目的:
- 提出一个创新的节能多机器人控制系统,EnergyWise,以解决目前VSLAM实施的局限性.
- 通过智能VSLAM激活,在复杂的大型环境中提高机器人的能效和定位精度.
- 在COVID-19大流行期间验证系统在现实世界消毒任务中的性能.
主要方法:
- 开发了基于ROS的EnergyWise多机器人系统,结合了节能选择器算法来控制VSLAM激活.
- 实施了一种新的2级扩展卡尔曼波器 (EKF) 方法,并集成超宽带 (UWB) 全球定位,以进行强大的姿势估计.
- 在一个大而复杂的实验场所部署了三台消毒服务机器人进行了为期10天的操作.
主要成果:
- 在长期的机器人操作过程中,实现了显著的54%的计算能耗减少.
- 保持3厘米的高定位精度,证明了系统在复杂环境中的有效性.
- 成功证明了系统在实际消毒应用中的能力.
结论:
- 拟议的EnergyWise系统为提高多机器人系统的能源效率提供了一个可行的解决方案.
- 智能VSLAM激活和强大的本地化机制对于可靠的长期机器人操作至关重要.
- 这种方法非常适合在动态和大规模环境中运行的服务机器人.
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