COLLABORATIVE: Planning Manipulation with Contact Under Uncertainty

研究了滚动和滑动接触摩擦任务的机器人运动规划(广义操作规划)。其目标是推导和使用多刚体力学和数学规划的新结果，以开发自动生成稳健反馈控制策略的技术。尽管几何、运动学和动力学模型的参数以及传感误差存在不确定性，但这些策略将确保在接触的情况下正确执行操作任务。当不能保证正确的任务执行时，次要目标是指定一组更紧但尽可能宽的不确定参数和检测错误的界限，如果满足，将保证正确执行。预期结果的应用领域包括工业装配、抓取和灵巧操作、视觉服务、医疗装配(例如髋关节置换)、虚拟现实和机械设计。为了测试所提出的方法的实用性和基本数学模型的有效性，将实现一个基于CAD的操作规划系统。自动生成的计划将使用真实设备(即，一个工业机器人和德克萨斯A&M公司提供的平面灵巧操作试验台)执行。此外，真正的问题和相关数据将由通用电气、波音和阿马里洛国家钚资源中心的同事提供。这项工作涉及到与教授的合作。德克萨斯农工大学计算机科学系的南希·阿马托和杰弗里·特林克尔。

This research studies robot motion planning for tasks involving rolling and sliding contact with friction (generalized manipulation planning). The goal is to derive and use new results in multi-rigid-body mechanics and mathematical programming to develop techniques for the automatic generation of robust feedback control strategies. These strategies will guarantee correct execution of manipulation tasks with contact despite uncertainty in the parameters of the geometric, kinematic, and dynamic models, and sensing errors. When correct task execution cannot be guaranteed, the secondary goal is to specify a set of tighter, but widest possible, bounds on the uncertain parameters and sensing errors, which if satisfied, would guarantee correct execution. Application domains for the expected results include industrial assembly, grasp acquisition and dexterous manipulation, visual serving, medical assembly (e.g., hip replacement), virtual reality, and mechanical design. To test the practicality of the proposed approach and the validity of the underlying mathematical models, a CAD-based, manipulation planning system will be implemented. Automatically generated plans will be executed with real devices (i.e., an industrial robot and a planar dexterous manipulation testbed available at Texas A&M). In addition, real problems and associated data will be provided by colleagues from General Electric, Boeing, and the Amarillo National Resource Center for Plutonium. The work involves a collaboration with Profs. Nancy Amato and Jeffrey Trinkle of the Department of Computer Science at Texas A&M University.