Human-centered Robot Manipulation Planning for Solving Object Handover Tasks in the Real-World

以人为中心的机器人操纵规划，解决现实世界中的物体移交任务

• 批准号: 2204528
• 负责人: Ahmed Qureshi
• 金额: $ 38.95万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2204528&HistoricalAwards=false
• 关键词: Human; centered; Robot; Manipulation; Planning

Robots aiming to assist people in their daily lives need to have robust skills in handing over arbitrary, unknown objects to and from their interacting partners in various environments. Older people, especially those with a disability, often have difficulty maneuvering and need assistance even for minor chores such as handing over the TV remote, fetching water bottles, and other items such as medicines. This need for assistance has become even clearer from the COVID-19 outbreak, requiring collaborative robots with object handover skills to keep the affected person and their caretakers at a safe distance. Similarly, such robot abilities in factories can significantly improve work efficiency by handing over various tools to and from their collaborating workers. However, despite the significance of having robots with object handover skills, such a fundamental task remains unsolved. This proposal presents a framework to solve the human-robot handover tasks with arbitrary daily-life objects in uncontrolled environments and explicitly considers the most-used items by patients with motor impairments such as Amyotrophic Lateral Sclerosis.The technical contributions of this proposal are divided into three research thrusts. First, a novel task-aware, 3D pose forecasting approach will be introduced to predict future poses of the full human body and their handheld objects from raw sensory information. During inference, various human body parts that are crucial for robot decision-making and control in solving human-robot object handover tasks will also be highlighted through learning-based attention models. Second, the proposal will formalize, represent, and learn the task-specific physical human-object and object-object interactions to predict socially feasible target object poses for handovers concerning the expected human behaviors and robot’s kinematic reachability during manipulation. Third, the predicted human behaviors and desired object handover poses will be used to determine human-friendly robot grasp and generate informed human-aware robot motion sequences. Finally, the proposed research thrusts will be integrated into a unified framework to solve human-to-robot and robot-to-human handover tasks with arbitrarily unknown objects from raw visual observations. The proposal’s outcomes will also exhibit new, proof-of-concept, human-robot handover demonstrations in the real-world using various most-used items by people with motor impairments.This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).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.

机器人旨在帮助人们日常生活，需要在各种环境中交出往返互动伙伴的任意，未知的对象方面具有强大的技能。老年人，尤其是那些残疾人，通常会很难动手，甚至需要诸如远程远程远程杂乱的琐事，取水瓶以及其他物品（例如药物）的帮助。这种对协助的需求已经变得更加明显，从199年的爆发中，需要具有对象切换技巧的协作机器人，以使受影响的人及其护理人员保持安全距离。同样，工厂中的这种机器人能力可以通过向其合作工人提供各种工具来显着提高工作效率。但是，尽管拥有具有对象切换技巧的机器人的意义，但这种基本任务仍未解决。该提案提出了一个框架，以在不受控制的环境中使用任意日常生物来解决人类机器人移交任务，并明确考虑有运动障碍患者（如肌萎缩性侧向硬化）的最常用的物品。该建议的技术贡献将其分为三个研究推力。首先，将引入一种新颖的任务感知，3D姿势预测方法，以通过原始感官信息来预测整个人体及其手持物体的未来姿势。在推断期间，对于机器人决策和控制人类机器人对象切换任务至关重要的各种人体部位也将通过基于学习的注意力模型来强调。其次，该提案将形式化，代表和学习特定于任务的物理人类对象和对象对象相互作用，以预测有关社会可行的目标对象，以构成有关预期人类行为的移交以及在操纵过程中机器人的运动式可及性。第三，预测的人类行为和所需的物体切换位置将用于确定对人类友好的机器人掌握并产生知情的人类意识到的机器人运动序列。最后，提议的研究推力将集成到一个统一的框架中，以通过原始视觉观察的任意未知对象来解决人与身驾驶的人对机器人和机器人对人类的移交任务。 The proposal’s outcomes will also exhibit new, proof-of-concept, human-robot handover demonstrations in the real-world using various most-used items by people with motor impairments.This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).This award reflects NSF's statutory mission and has been deemed值得通过基金会的智力优点和更广泛的影响审查标准来通过评估来支持。