NRI: Considerate Co-robot Intelligence through Ubiquitous Human State Awareness

该项目为辅助生活环境中的机器人伴侣开发了一种新型的社会智能。 这种新的智能使机器人能够了解一个人的日常活动和位置，而无需不断地跟踪他或她。这种人类感知能力使机器人能够自由地完成日常工作，同时能够更主动和有效地参与人类。 大量人口可以从该项目的成果中受益，特别是在家中需要帮助和陪伴的老年人和病人。 此外，工作场所的人们也可以从这个项目中受益，因为机器人同事可以提供具有人类意识的日常服务和紧急援助。 拟议的教育活动将通过丰富一系列本科和研究生课程的课程内容，提高人们对机器人研究的认识。 通过外联活动，它将激励未来和当前的大学生攻读科学和工程学位和职业。本项目的目标是开发新的理论/算法框架和开放的硬件/软件平台，这种类型的体贴的合作机器人智能。 所提出的方法是基于无处不在的人的意识，机器人的能力，知道一个人的活动和位置在室内环境中，而不使用板载传感器。这种能力是通过可穿戴传感和计算从人性化的角度来实现的。主要研究工作包括四个部分：协作机器人3D语义映射;人类活动和位置推断;活动预测和行为异常检测;使用开放硬件/软件平台的实验评估。将进行一个案例研究，以评估拟议的体贴合作机器人智能在老年人跌倒预防，检测和干预的有效性。

This project develops a new type of social intelligence for robot companions in assisted living environments. This new intelligence allows a robot to learn a person's daily activity and location without constantly following him or her. Such a human-aware capability frees the robot to do its daily routine work, while being able to attend the human more proactively and effectively. A large population can benefit from the outcome of this project, especially the elderly and patients who need assistance and companionship in their homes. In addition, people in their work places can also benefit from this project, since robot co-workers can provide routine service and emergency assistance with such human-awareness. The proposed educational activities will raise more awareness of robot research through curriculum enrichments in a series of undergraduate and graduate courses. Through the outreach activities, it will stimulate prospective and current college students to pursue degrees and careers in science and engineering. The objective of this project is to develop the new theoretical/algorithmic framework and the open hardware/software platform for this type of considerate co-robot intelligence. The proposed method is based on ubiquitous human awareness-a robot capability of knowing a person's activity and location in an indoor environment without using onboard sensors. This capability is realized through wearable sensing and computing from a human-based perspective. The major research efforts consist of four parts: co-robot 3D semantic mapping; human activity and location inference; activity prediction and behavioral anomaly detection; experimental evaluation using open hardware/software platforms. A case study will be conducted to evaluate the effectiveness of the proposed considerate co-robot intelligence in elderly fall prevention, detection and intervention.