RI: Medium: Collaborative Research: Real-Time Continuum Manipulation

这个项目的目标是研究在结构较少、具有很大不确定性甚至未知的环境中使用新型连续体机器人进行根本新型机器人操作的可能性。连续体机器人，如躯干/触手机器人手臂，在许多意义上是双重的？与传统的机器人操纵器(由关节臂和夹爪或手组成)相比，具有相对较低的精度但柔顺性较高：*其固有的灵活性和柔顺性提供了更大的前景，使其能够在更大范围(数量级)的物体的不精确和不确定的条件下进行灵活操作，对象的大小和重量、许多不同的形状和具有非常不同的物理特征(刚性、软性、灵活性等)。*另一方面，其固有的缺乏精确度使得传统的规划和控制机器人操作器的方法不适合使用连续体机器人进行操作。该项目开创了由单个连续体机器人自主操纵具有很大不确定性的对象这一基本问题的研究。它提出了一种新的整体方法，在实时感知和大环境不确定性的情况下，集成了实时自适应规划和鲁棒控制方案。接下来，它扩展了基本方法，以解决在公共环境中工作的多个连续体机器人，其中每个机器人不需要知道另一个机器人的运动。这项研究将理论/算法开发与现实世界的验证相结合，在配备传感器的真实躯干/触手机器人的实验试验台上进行了验证。这些成果将通过出版物、自由软件和真实世界的演示积极传播，以影响研究、教育和应用。

The goal of this project is to investigate the potential of fundamentally new modes of robotic manipulation using novel continuum robots in less-structured environments with large uncertainties and even unknowns. A continuum robot, such as a trunk/tentacle robot arm, is in many senses ?dual? to a traditional robot manipulator (consisting of an articulated arm and a gripper or hand), featuring relatively low precision but high compliance: * Its inherent flexibility and compliance offer greater promise to enable deft manipulation under imprecise and uncertain conditions of objects over a wider range (orders of magnitude) of size and weight, of many different shapes, and with widely different physical characteristics (rigid, soft, flexible, etc.).. * On the other hand, its inherent lack of precision renders the traditional approaches to planning and control of robot manipulators unsuitable for manipulation with continuum robots. This project pioneers the study of the basic problem of autonomous manipulation of an object with much uncertainty by a single continuum robot. It introduces a novel and holistic approach that integrates real-time adaptive planning and robust control schemes under real-time sensing and large environmental uncertainty. It next extends the basic approach to address multiple continuum robots working in a common environment, where each robot needs not know the motion of another robot. The research combines theoretical/algorithmic development with real-world validation on an experimental test bed with real trunk/tentacle robots equipped with sensors. The results will be actively disseminated through publications, free software, and real-world demos to impact research, education, and applications.