SBIR Phase I: Robotic Pavement Marking

SBIR 第一阶段：机器人路面标线

• 批准号: 2014644
• 负责人: Samuel Bell
• 金额: $ 22.46万
• 依托单位: RoadPrintz, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-15 至 2020-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2014644&HistoricalAwards=false
• 关键词: SBIR; Phase; Robotic; Pavement; Marking

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is increasing road safety by making effective visual street markings more affordable and accessible. This will be achieved through the design of an intelligent mobile robotic system using advanced localization and machine vision to automate the process of producing road markings that are precisely created and accurately placed. The project will push the limits of accuracy of geolocation of robotic material dispensing via a mobile platform. The resulting system will dramatically improve efficiency of road painting, offering greater precision, speed, and flexibility while reducing risk to operators, reducing traffic congestion, and supporting greater road safety through enhanced markings. Success in this effort will have applications beyond road painting, including automated material dispensing more broadly, and intelligent mobile manipulation for manufacturing.This Small Business Innovation Research (SBIR) Phase I project will address the challenges of automating creation of specific road markings at desired locations. The research will include: design optimization of the mobile robot for large-area, precision painting; sensor fusion for precision localization of the mobile robot; precision hand/eye calibration; and development of adaptive coverage algorithms capable of executing complex fill patterns adjusted spatially based on localization, machine vision and 3-D surface scanning.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是通过使有效的视觉街道标记更便宜和更容易获得来提高道路安全。 这将通过设计一个智能移动的机器人系统来实现，该系统使用先进的定位和机器视觉，使精确创建和准确放置的道路标记的制作过程自动化。 该项目将通过移动的平台突破机器人材料分配地理定位的准确性极限。 由此产生的系统将大大提高道路油漆的效率，提供更高的精度，速度和灵活性，同时降低运营商的风险，减少交通拥堵，并通过增强标记来支持更高的道路安全。 这一努力的成功将带来道路油漆以外的应用，包括更广泛的自动材料分配和制造业的智能移动的操纵。这一小型企业创新研究（SBIR）第一阶段项目将解决在所需位置自动创建特定道路标记的挑战。研究将包括：用于大面积精密喷涂的移动的机器人的设计优化;用于移动的机器人的精确定位的传感器融合;精确的手/眼校准;以及开发能够执行基于定位在空间上调整的复杂填充图案的自适应覆盖算法，机器视觉和3-该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准。