SHB: Small: Computing Robot Motions for Home Healthcare Assistance

数以百万计的美国人无法独立进行穿衣打扮等日常生活活动，而且随着美国S老龄化和残疾人口的增加，这一数字正在迅速上升。这项研究的重点是设计和开发新的算法和软件系统，帮助个人机器人自主计算安全动作，以帮助患有ADL的残疾人和老年人。所提出的框架使用动觉演示来教机器人期望的运动轨迹来完成几个特定的ADL辅助任务。在这些演示的基础上，研究重点是开发新的计算方法来提取期望运动轨迹的任务约束，将基于高斯混合模型的学习方法与机器学习和3D配准方法相结合。这个项目的一个关键要素是研究可变形地记录和概括不同形状和大小的个体的运动轨迹和任务约束的方法。为了在动态的现实环境中生成安全的计划，该研究提出了新的高度并行的算法，该算法有效地利用现代通用图形处理单元(GPU)的能力来在不确定环境中进行实时规划。该框架使用铰接式人体模型试验台进行评估。该项目汇集了一个具有计算机科学、机器人学和职业治疗专业知识的跨学科团队。该项目通过社区外联活动将研究与教育结合起来。从长远来看，拟议研究中开发的方法可能会产生广泛的社会效益，帮助个人机器人帮助患有ADL的残疾人和老年人，使他们能够安全地呆在家里，而不是搬到昂贵的机构。

Millions of Americans are unable to independently perform activities of daily living (ADLs) such as dressing and grooming, and this number is rising rapidly as America?s aging and disabled population increases. This research focuses on designing and developing new algorithms and software systems that would help enable personal robots to autonomously compute safe motions to assist disabled and elderly individuals with ADLs. The proposed framework uses kinesthetic demonstrations to teach the robot desirable motion trajectories to accomplish several specific ADL assistance tasks. Based on these demonstrations, the research focuses on developing new computational methods to extract task constraints for desirable motion trajectories using learning methods based on Gaussian mixture models in conjunction with machine learning and 3D registration methods. A key element of this project involves investigation of methods to deformably register and generalize the motion trajectories and task constraints across individuals of different shapes and sizes. In order to generate safe plans in dynamic real-world settings, the proposed research investigates new highly parallel algorithms that effectively utilize the power of modern general purpose graphics processing units (GPUs) for real-time planning in uncertain environments. The framework is evaluated using articulated mannequin testbeds.This project brings together an interdisciplinary team with computer science, robotics, and occupational therapy expertise. The project integrates research with education through community outreach activities. In the long term, the methods developed in the proposed research could have broad societal benefits by helping enable personal robots to assist disabled and elderly individuals with ADLs, allowing them to safely stay in their homes rather than moving to costly institutions.