NRI: Collaborative Research: A Dynamic Bayesian Approach to Real Time Estimation and Filtering in Grasp Acquisition and Other Contact Tasks (Continuation)

NRI：协作研究：抓取采集和其他接触任务中实时估计和过滤的动态贝叶斯方法（续）

• 批准号: 1537257
• 负责人: Siwei Lyu
• 金额: $ 22.1万
• 依托单位: SUNY at Albany
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1537257&HistoricalAwards=false
• 关键词: NRI; Collaborative; Research; Dynamic; Bayesian

A current weakness of robots is their inability to quickly and reliably perform contact tasks in unstructured environments. The goal of this project, which represents a collaboration between faculty at two partner institutions, is to alleviate this shortcoming by developing techniques that will afford robots accurate real-time perception in tasks exhibiting intermittent contact. Project outcomes will have a strong impact in manipulation tasks, as robots become more capable and autonomous. The PIs also expect successful applications in other areas, for instance to drive real-time haptic displays in augmented reality systems, to extract human manipulation strategies from observed kinesthetic demonstrations, and to identify model parameters to improve simulation accuracy, not to mention in advancing the level of autonomy for space and undersea exploration. Additional applications outside of robotics are anticipated in situations where a system experiences abrupt state transitions and the goal is either state estimation or real-time feedback control (e.g., chemical, financial, and geological systems). The PIs' labs have a track record of supporting women and under-represented minorities, and the research will be integrated into a variety of pedagogical activities at the graduate and undergraduate level on both campuses.In previous work the team proposed the DBC-SLAM framework, in which continuous states (i.e., poses, velocities and contact impulses), and discrete contact states (i.e., contact-noncontact and stick-slip) of the manipulated objects, are tracked and important model parameters are estimated. In this research, they will extend that work significantly in two directions. First, they will design new parallel, anytime complementarity problem (CP) solvers in order to attain real-time performance. Second, they will enhance the dynamic Bayesian models in DBC-SLAM to allow the use of point-cloud observations and more complex geometric models of the objects, robot links, and environment. The intellectual merit of the project lies in three main activities: first, the creative, yet rigorous, technical process of designing perception algorithms based on fundamental first principles of nonsmooth mechanics and Bayesian estimation in a way that can utilize point-cloud data; second, achieving real-time performance by exploiting the mathematical structure and properties of both the nonsmooth multibody dynamics and CPU/GPU computing systems; and third, pursuing the first two activities in a way that sheds light on the trade-offs between estimation accuracy and speed.

机器人目前的一个弱点是无法在非结构化环境中快速可靠地执行接触任务。这个项目代表着两个合作机构的教职员工之间的合作，目的是通过开发技术来缓解这一缺陷，这些技术将使机器人能够在显示出间歇性接触的任务中进行准确的实时感知。随着机器人变得更有能力和自主性，项目成果将对操纵任务产生强烈影响。PI还希望在其他领域取得成功，例如在增强现实系统中驱动实时触觉显示，从观察到的动觉演示中提取人类操纵策略，以及识别模型参数以提高模拟精度，更不用说在提高空间和海底探索的自主性水平方面。在系统经历突然的状态转换并且目标是状态估计或实时反馈控制(例如，化学、金融和地质系统)的情况下，预计在机器人技术之外的其他应用。在之前的工作中，该团队提出了DBC-SLAM框架，其中跟踪了被操纵对象的连续状态(即姿势、速度和接触脉冲)和离散接触状态(即接触-非接触和粘滑)，并估计了重要的模型参数。在这项研究中，他们将在两个方向上显著扩展这项工作。首先，他们将设计新的并行、随时互补问题(CP)求解器，以获得实时性能。其次，他们将增强DBC-SLAM中的动态贝叶斯模型，以允许使用点云观测和对象、机器人链接和环境的更复杂的几何模型。该项目的智力价值在于三个主要活动：第一，基于非光滑力学和贝叶斯估计的基本第一原理，以一种可以利用点云数据的方式设计感知算法的创造性而又严格的技术过程；第二，通过利用非光滑多体动力学和CPU/GPU计算系统的数学结构和特性来实现实时性能；第三，以一种能够在估计精度和速度之间进行权衡的方式追求前两项活动。