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SBIR Phase I: Assistive Robots for Personal Care and COVID-19 Protection

SBIR Phase I: Assistive Robots for Personal Care and COVID-19 Protection
SBIR 第一阶段:用于个人护理和 COVID-19 防护的辅助机器人
批准号:
2036684
负责人:
Michael Dooley
金额:
$25.58万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-01-01 至 2024-03-31

项目摘要

项目成果

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中文摘要
翻译
这个小型企业创新研究(SBIR)第一阶段项目的更广泛的影响/商业潜力推进了新兴的基于视觉的自主导航技术的发展,为低成本/高性能的个人辅助机器人开辟了新的可能性。机器人解决方案使行动不便的个人能够对其环境拥有更多的代理权,并享受更高的生活质量。这有助于解决老年人和急性病后护理患者护理人员严重短缺的问题,使个人能够保持独立,扩大护理人员的影响,并降低家庭和设施环境中的护理费用。 此外,通过在COVID-19护理环境中提供负担得起且可靠的隔离支持,拟议的解决方案可以帮助减少与COVID-19疾病管理相关的财务负担并增加公共卫生成果。核心机器人解决方案仅在美国就有1100万高需求用户的直接可寻址市场,预计产品发布后五年的收入约为16.5亿美元。进一步的商业化机会来自于将部分已开发的导航技术授权用于其他机器人应用,以及围绕核心机器人解决方案开发一个互补产品生态系统。这一小型企业创新研究第一阶段项目旨在实现新一代辅助服务机器人,其性能与商用机器人相当,但对于个人使用和个人护理应用来说,价格要便宜得多。该创新采用了增强现实的新兴视觉定位技术,使用低成本的消费级电子产品为移动的机器人提供强大的导航,同时解决了视觉定位系统的一个关键限制,即外部照明条件和环境中的其他变化会显著影响其性能。这项创新通过硬件和软件的结合来解决这些挑战,这些硬件和软件可以学习和稳定环境中最高价值的视觉元素,以在照明条件和长时间内保持持久性-这是使辅助机器人具有成本效益以大规模采用的关键发展。研究目标包括:充分开发和集成视觉持续系统,以在目标操作环境的照明条件和视觉特性的代表性范围内实现准确和可复制的机器人导航性能,并将所得解决方案与最先进的技术进行基准测试,以证明其上级的性能(即,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。
英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project advances the state-of-the art of an emerging class of vision-based, autonomous navigation technologies to open new possibilities for low-cost/high-performance personal assistive robots. The robotics solution enables mobility-impaired individuals to have more agency over their environment and enjoy a higher quality-of-life. This helps address the severe shortage of caregivers for the elderly and post-acute care patients by empowering individuals to maintain their independence, extending the impact of caregivers, and reducing the cost of care in both home and facility settings. Additionally, by providing affordable and reliable isolation support in COVID-19 care settings, the proposed solution can help decrease the financial burden and increase the public health outcomes associated with COVID-19 disease management. The core robotics solution has an immediate addressable market of 11 million high-needs users in the U.S. alone, with projected revenues of roughly $1.65 Billion five years after product launch. Further commercialization opportunities come from licensing parts of the developed navigation technology for other robotics applications and developing an ecosystem of complementary products around the core robotics solution.This Small Business Innovation Research Phase I project seeks to enable a new generation of assistive service robots that are comparable to commercial robots in performance, but significantly more affordable for individual use and personal care applications. The innovation adopts emerging visual positioning technologies from Augmented Reality to enable robust navigation for mobile robots using low-cost, consumer-grade electronics, while addressing a key limitation of visual positioning systems namely, that external lighting conditions and other changes in an environment can dramatically impact their performance. The innovation addresses these challenges via a combination of hardware and software that learns and stabilizes the highest value visual elements of the environment to maintain persistency across lighting conditions and long periods of time — a development critical to making assistive robots cost-effective for adoption at a large scale. Research objectives include: fully developing and integrating the visual persistency system, to achieve accurate and replicable robot navigation performance across a representative range of lighting conditions and visual characteristics of the target operating environments and benchmarking the resulting solution against state-of-the art technologies, to demonstrate its superior performance (i.e., it can successfully localize in at least 90% of cases where other solutions fail).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.
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