CAREER: Towards General-Purpose Manipulation of Deformable Objects through Control and Motion Planning with Distance Constraints

点击翻译按钮获取中文摘要

This project seeks to advance the capabilities of autonomous robots in environments such as factories, hospitals, and homes. To be effective in such settings, robots need to manipulate many kinds of deformable objects, such as cloth, string or wires, and plant or animal tissue. Giving robots the ability to manipulate such objects has the potential to revolutionize the use of robots in several application domains: In manufacturing, allowing robots to pack boxes and handle food and fabric; in medicine, allowing robots to perform tedious tasks in surgery and make hospital beds; and in service, allowing robots to handle clothes and prepare food. However, such tasks are beyond the current state-of-the-art, largely because deformable objects are difficult to model and control. This project will develop new theory, validated with extensive experimentation, that aims to model deformable objects in ways that are amenable to both planning and control. This project will also use manipulation of deformable objects as a motivating problem for students studying robotics at the undergraduate and graduate levels, and in K-12 outreach.This project investigates the fundamentals of modeling, control, and motion planning for deformable objects. This problem is challenging because deformable objects have large state spaces, are extremely-underactuated, and motion planning for these objects requires numerical simulation, which can be computationally expensive and inaccurate. The main hypothesis of this project is that these challenges can be overcome by representing the object and task in terms of distance constraints, which represent allowable distances between parts of the deformable object as well as between the object and parts of the environment, and formulating control and planning methods based on this representation. The expected outcome of this research is an enhanced ability of robots to perform useful tasks, based on a better understanding of deformable object manipulation and a set of broadly-applicable experimentally-verified controllers, planning building-blocks, and planning algorithms.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.