I-Corps: Healthcare Service Robots

过去的机器人商业化工作一直以移动基地为主。机械臂往往呆在笼子里或远离人类（例如，制造业）。 I-Corps 团队希望将移动机械手带入人类环境中，以执行人们认为不需要的重复性手动任务。该团队的最初假设是表面清洁就是这样的任务之一。预计表面卫生自动化可以以更高的频率实现更多的表面覆盖，创造一个更卫生的环境，减少疾病。这种机器人还有可能使不需要的体力劳动自动化，并减少与重复性体力劳动相关的人体伤害。将需要较低技能或体力劳动的任务自动化可以让人类更多地关注高技能劳动力，从而缓解劳动力短缺的问题。 因此，该项目旨在定义智能移动机器人的商业应用。可供更多人使用的无处不在、友好的机器人也将理想地激励年轻一代接受 STEM 教育，从而培养出技能更高、更具竞争力的美国劳动力。该项目旨在定义带有手臂的智能移动机器人（移动机械手）的商业应用。基于八年多的人机交互研究成果，该团队打算应用演示学习（LfD）算法，使没有机器人经验的最终用户可以对机器人进行编程，这可以通过直观的社交对话来完成。机器人还需要在人类面前以透明且可预测的方式自主行动，这需要发展具有社会意识的操纵和导航行为。 I-Corps 计划期间团队的大部分方法将致力于采访客户发现，最初的目标客户是医疗保健机构。为了验证这一细分市场，该团队打算访问医院和长期护理机构，以确定客户的痛点以及采用机器人技术的流程和障碍。此外，团队计划采访专家、参加会议并进行文献检索，以更好地了解该领域；并且，到 I-Corps 计划结束时，它预计将定义机器人必须执行的一组关键任务，以便为我们的目标客户群提供价值。这些任务将定义机器人硬件和软件的最小可行设计的规范。

Past commercialization efforts for robotics have been dominated by mobile bases. Robotic arms tend to stay in cages or far from humans (e.g., manufacturing). This I-Corps team wants to bring mobile manipulators to human environments to perform repetitive manual tasks that people find undesirable. The team's initial hypothesis is that surface cleaning is one such task. It is anticipated that automation of surface sanitation can achieve more surface coverage with higher frequency, creating a more sanitary environment that reduces illness. Such a robot also has the potential to automate undesirable manual labor, as well as reduce human injuries associated with repetitive physical work. Automating tasks requiring lower skills or manual labor could ameliorate the labor shortage by allowing humans to focus more on high-skilled labor. This project, therefore, aims to define a commercial application for an intelligent mobile robot. The presence of ubiquitous, friendly robots that can be used by more people will ideally also inspire younger generations to pursue STEM education, leading to a more skilled and competitive American workforce. This project aims to define a commercial application for an intelligent mobile robot with an arm (mobile manipulator). Based on over eight years of research results in Human-Robot Interaction, the team intends to apply learning from demonstration (LfD) algorithms to make the robot programmable by end users with no robotics experience, which can be accomplished using an intuitive social dialogue. The robot will also need to act autonomously in the presence of humans in a way that is transparent and predictable, which requires developing manipulation and navigation behavior with social awareness. The bulk of the team's methodology during the I-Corps program will be dedicated to interviews for customer discovery, with an initial target customer as health care establishments. To validate this segment, the team intends to visit hospitals and long-term care facilities to identify customer pain points, as well as processes and barriers for adopting robotic technology. In addition, the team plans to interview experts, attend meetings, and conduct literature searches to better understand the domain; and, by the end of the I-Corps program, it expects to have defined a set of key tasks that the robot must perform to provide value to our target customer segment. These tasks will define specifications for a minimum viable design of the robot hardware and software.