SBIR Phase II: Robotic Pavement Marking

SBIR 第二阶段：机器人路面标线

• 批准号: 2111885
• 负责人: Samuel Bell
• 金额: $ 99.99万
• 依托单位: RoadPrintz, Inc.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2111885&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Robotic; Pavement

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project seeks to significantly reduce the number of injuries or deaths suffered by pavement marking workers on public streets and roads, while increasing the efficiency and lowering costs by using an operator-driven, truck-mounted, mobile robotic pavement marking system. Robotic painting allows workers to remain in the safety of the truck cab, protecting them from traffic. Increased efficiency will help to minimize work zone congestion and duration, while reduced costs will enable safer and more productive streetscapes for the general public. Studies have repeatedly confirmed that streetscapes with a high density of transverse marking features such as shared center turning lanes, dedicated bike lanes with separation buffer zones, and pedestrian-friendly crosswalks result in measurable public health benefits, enhanced quality of life, increased commercial activity, and, counterintuitively, more efficient traffic flow with fewer collisions. The project will also better enable precise placement of new markings and precise overpainting of worn or eroded markings, both important factors for connected and autonomous vehicles. An earlier phase of the project has already resulted in enhancements to camera calibration techniques for machine vision.This Small Business Innovation Research (SBIR) Phase II project seeks to build on a successful Phase I effort to enable a commercially-viable robotic road painting system that addresses the need to protect the lives of human workers engaged in the dangerous task of stenciling roadway markings such as turn arrows or bike symbols. The project may also improve the accuracy and ease of application of markings needed to support autonomous vehicle-ready roadways. The research will apply advanced software, machine vision, an augmented-reality user interface, and proprietary robotic trajectory planning technologies to support ultraprecision painting in the real-world environment while keeping human workers safe in the cab of the operator-driven truck upon which the robot is mounted. The solution will enable robots to paint previously unmarked pavement and to repaint existing marks. The combined hardware and software solution will be capable of recording all planned and completed markings in a cloud-hosted database—an innovation that will streamline the processes. The technology will also form a cloud-based standard for mapping and recording universal road markings and support the ability of autonomous vehicles to operate safely. While much of the research can initially be performed in simulation, significant real-world testing and validation will be required as well.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.

这一小型企业创新研究（SBIR）第二阶段项目的更广泛影响/商业潜力旨在显著减少公共街道和道路上路面标记工人的伤亡人数，同时通过使用操作员驱动的、卡车安装的、移动的机器人路面标记系统来提高效率并降低成本。机器人喷漆使工人能够安全地留在卡车驾驶室内，保护他们免受交通事故的影响。 提高效率将有助于最大限度地减少工作区的拥堵和持续时间，而降低成本将为公众提供更安全、更富有成效的街景。研究一再证实，具有高密度横向标记特征的街景，如共享中心转弯车道，带有隔离缓冲区的专用自行车道，以及对行人友好的人行横道，可以带来可衡量的公共卫生效益，提高生活质量，增加商业活动，以及与直觉相反的，更有效的交通流量，减少碰撞。该项目还将更好地实现新标记的精确放置和磨损或侵蚀标记的精确覆盖，这对于联网和自动驾驶车辆都是重要因素。该项目的早期阶段已经实现了机器视觉摄像机校准技术的增强。这个小型企业创新研究（SBIR）第二阶段项目旨在建立在成功的第一阶段工作的基础上，实现商业可行的机器人道路喷涂系统，以满足保护从事危险任务的人类工人生命的需求，这些危险任务包括印刷道路标记，如转向箭头或自行车符号。该项目还可以提高支持自动驾驶汽车道路所需的标记的准确性和易用性。该研究将应用先进的软件、机器视觉、增强现实用户界面和专有的机器人轨迹规划技术，以支持在现实环境中进行超精密喷漆，同时确保工人在操作员驾驶的卡车驾驶室中的安全。该解决方案将使机器人能够油漆以前没有标记的路面，并重新油漆现有的标记。结合硬件和软件的解决方案将能够记录所有计划和完成的标记在云托管数据库-创新，将简化流程。 该技术还将形成一个基于云的标准，用于绘制和记录通用道路标记，并支持自动驾驶汽车安全运行的能力。虽然许多研究最初可以在模拟中进行，但也需要进行大量的真实世界测试和验证。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。