NRI: FND: Dexterous Manipulation Using Multi-Serial Manipulator Systems with Real-Time Compliance Modulation

NRI：FND：使用具有实时顺应性调制的多串行机械手系统进行灵巧操纵

基本信息

批准号：
2024554
负责人：
Joseph Schimmels
金额：
$ 75万
依托单位：
Marquette University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024554&HistoricalAwards=false
关键词：
NRI FND Dexterous Manipulation Using

项目摘要

This National Robotics Initiative project will promote the progress of science and advance the national health, prosperity and welfare by discovering foundational scientific knowledge needed to allow robots to achieve human-like dexterity in constrained manipulation tasks. Current robots are better than people at executing desired motions in free space, but they are not nearly as adept at performing tasks in which motion is constrained in some way. Examples of such tasks in everyday life include peeling potatoes, opening a bottle, closing a container, cleaning a surface, or assembling furniture. Robots have great difficulty in performing these types of tasks because inevitable uncertainties in object exact locations often cause robot commanded positions to conflict with physical constraints, resulting in excessive contact forces and task failure. This award supports fundamental research into improving robot dexterity by providing a robot system the human-like ability to continuously adjust its inherent mechanical behavior as a task progresses so that it can be compliant in directions that are constrained and to be stiff in directions for which the commanded motion is needed to complete the task. Human-like dexterous manipulation is needed for robots to be widely used in senior living-assistance, agriculture, construction, space exploration, healthcare, nuclear remediation, and manufacturing. The robustness of the approach will be demonstrated in a manufacturing assembly testbed application. Therefore, results from this research will provide broad benefit to society and the U.S. economy. The technologies developed will be in the areas of mechanical engineering (kinematics, dynamics, and control) and computer science and will engage and educate students, including members of underrepresented groups, in these areas of national need.To obtain improved dexterity, multiple collaborating serial manipulators will be used to achieve a desired time-varying compliance, one specifically optimized for a given task so that it is properly executed despite uncertainties in task geometry and associated physical constraints. The compliance will be passively realized using variable stiffness actuators in each joint of the multi-manipulator system. With this optimized modulated passive compliance approach, the inherent mechanical behavior of the robot system is guaranteed to regulate contact force to not exceed specified limits and to move as desired to attain task objectives. The three specific aims of this research project are: 1) identify necessary and sufficient conditions and general synthesis procedures to achieve any specified passive compliance for different multi-serial manipulator topologies, 2) identify procedures for continuously and simultaneously attaining the desired object position and passive elastic behavior as an object is moved by redundant collaborating robots for different multi-serial manipulator topologies, and 3) demonstrate customizable dexterous manipulation using a three-finger planar robot hand with modulated passive compliance (using novel antagonistic tendon-driven variable stiffness actuators) performing a variety of different planar assembly tasks quickly and reliably.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.

这个国家机器人倡议项目将通过发现允许机器人在受限的操纵任务中实现类似人类的灵活性所需的基础科学知识来促进科学的进步，并促进国家健康，繁荣和福利。当前的机器人比在自由空间中执行所需动作的人要好，但是它们不太擅长执行运动以某种方式限制的任务。日常生活中此类任务的例子包括剥离土豆，打开瓶子，关闭容器，清洁表面或组装家具。机器人在执行这类任务方面有很大的困难，因为在对象中不可避免的不确定性通常会导致机器人指挥位置与物理约束冲突，从而导致过度接触力和任务失败。该奖项通过提供机器人系统来支持改善机器人敏捷的基本研究，即随着任务的进行，可以连续调整其固有的机械行为的能力，以便它可以符合受到限制的方向，并在指挥运动中僵硬地牢固地完成任务以完成任务。需要在高级生活辅助，农业，建筑，太空探索，医疗保健，核补救和制造业中广泛使用人类的灵巧操纵。该方法的鲁棒性将在制造组装测试台应用中证明。因此，这项研究的结果将为社会和美国经济带来广泛的好处。开发的技术将在机械工程（运动学，动力学和控制）和计算机科学领域以及计算机科学领域，并将在国家需求的这些领域中吸引和教育学生，包括代表性不足的群体的成员，以提高灵活性，将使用多个协作的串行操纵器来实现一项适当的任务，以实现一项适当的任务，以实现适当的任务，以使其达到适当的任务，以使其适用于任务，这是一个适当的任务，它可以实现这一任务，以实现这一任务，以实现既定的任务，以实现这一任务，以实现这一任务。几何和相关的物理约束。合规性将使用多个操纵器系统的每个关节中的可变刚度执行器被动地实现。通过这种优化的调制无源合规方法，保证机器人系统的固有机械行为可以调节接触力以不超过指定的限制，并根据需要移动以实现任务目标。该研究项目的三个具体目的是：1）确定必要和足够的条件和一般合成程序，以实现任何针对不同的多族式操纵器拓扑来实现任何特定的被动依从性，2）确定持续且同时获得所需的物体位置和被动弹性行为作为对象的连续和同时进行的冗余合作的多种式机器人的启示，并以多种多样的方式移动。使用具有调制的被动合规性（使用新型拮抗肌腱驱动的可变刚度执行器）进行调制的三指平面机器人手来执行各种不同的平面装配任务。该奖项反映了NSF的法定任务，并通过基金会的知识优点和广泛的影响来反映NSF的法定任务。