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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.

这个国家机器人计划项目将促进科学的进步，并通过发现所需的基础科学知识，使机器人在受限的操作任务中实现类似人类的灵活性，促进国家的健康，繁荣和福利。目前的机器人在自由空间中执行所需动作的能力比人类更好，但在执行运动受到某种限制的任务方面，它们几乎没有人类那么熟练。日常生活中的此类任务的示例包括削土豆皮、打开瓶子、关闭容器、清洁表面或组装家具。机器人在执行这些类型的任务时有很大的困难，因为对象精确位置的不可避免的不确定性往往会导致机器人命令的位置与物理约束相冲突，从而导致过度的接触力和任务失败。该奖项支持通过提供机器人系统的类似人类的能力来提高机器人灵活性的基础研究，随着任务的进展不断调整其固有的机械行为，以便它可以在受约束的方向上顺应，并在完成任务所需的指令运动方向上保持刚性。机器人需要像人类一样灵巧的操作，以广泛应用于老年人生活辅助，农业，建筑，太空探索，医疗保健，核修复和制造业。该方法的鲁棒性将在制造装配测试平台应用中得到证明。因此，这项研究的结果将为社会和美国经济提供广泛的利益。开发的技术将在机械工程领域（运动学，动力学和控制）和计算机科学，并将吸引和教育学生，包括代表性不足的群体的成员，在这些国家需要的领域。为了获得改善的灵活性，多个合作的串行操纵器将用于实现所需的随时间变化的顺应性，一种是针对给定任务而特别优化的，使得尽管任务几何形状和相关联的物理约束中存在不确定性，但其仍被正确地执行。在多机械臂系统的每个关节中使用可变刚度致动器将被动地实现顺应性。通过这种优化的调制被动顺应性方法，保证了机器人系统的固有机械行为，以调节接触力不超过指定的限制，并根据需要移动，以达到任务目标。该研究项目的三个具体目标是：1）识别必要和充分条件以及一般合成过程，以实现不同多系列操纵器拓扑的任何指定的被动顺应性，2）识别当对象由不同多系列操纵器拓扑的冗余协作机器人移动时用于连续地和同时地获得期望的对象位置和被动弹性行为的过程，以及3）使用具有调制被动顺应性的三指平面机器人手（使用新型对抗性腱驱动变刚度致动器）快速可靠地执行各种不同的平面装配任务，展示可定制的灵巧操作。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。