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: LABRADOR SYSTEMS, INC.
• 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
• 起止时间: 2021-01-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2036684&HistoricalAwards=false
• 关键词: SBIR; Phase; Assistive; Robots; Personal

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.

这项小型企业创新研究（SBIR）I阶段项目的更广泛的影响/商业潜力推动了新兴类型的基于视觉的自主导航技术的最先进，以开放针对低成本/高成本个人辅助机器人的新可能性。机器人解决方案使行动不便的人能够在环境上拥有更多的代理，并享受更高的生活质量。这有助于解决老年人和急性护理患者的严重短缺，通过授权个人保持独立性，扩大护理人员的影响并降低家庭和设施环境中的护理成本。此外，通过在COVID-19的护理环境中提供负担得起且可靠的隔离支持，该建议的解决方案可以帮助减少财务燃烧并增加与Covid-19-19-19疾病管理相关的公共卫生结果。仅在美国，核心机器人解决方案就会立即面向1100万高需求用户的可寻址市场，预计产品发布后五年后约16.5亿美元。进一步的商业化机会来自为其他机器人应用的开发导航技术的许可部分，并开发围绕核心机器人解决方案的互补产品的生态系统。本小型企业创新研究阶段I项目旨在使新一代的辅助服务机器人能够与商业机器人相提并论，但要获得更高的个人使用和个人护理应用程序。这项创新采用了从增强现实的新兴视觉定位技术，可以使用低成本，消费级电子设备为移动机器人提供强大的导航，同时解决了视觉定位系统的关键限制，即外部照明条件和环境中的其他变化可以极大地影响其性能。这些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的最高价值视觉元素，以在照明条件和长时间的范围内保持持久性，这对于使辅助机器人成本效益至关重要。研究目标包括：完全开发和整合视觉持久性系统，以在代表一系列照明条件和目标操作环境的一系列范围内实现准确，可复制的机器人导航性能，并基准对抗最先进的艺术技术的最终解决方案，以证明其出色的绩效（即，它可以成功地在案件中取得了90％的统计范围，并且在其他案件中都可以裁定，并且在其他方​​面进行了统计。使用基金会的智力优点和更广泛的影响审查标准通过评估来支持。