摘要
由一名新闻记者-机器人与机器学习每日新闻编辑-调查人员讨论机器人学的新发现。根据NewsRx记者在深圳的新闻报道，研究表明：“本文探讨了动态操作中最具挑战性的任务之一——捕捉大动量运动物体。除了准静态操作之外，处理高动态物体可以显著提高机器人与周围环境的互动能力。”本研究经费来源于国家自然科学基金(NSFC)。记者从哈尔滨科技大学的研究中得到一句话:“然而,快速移动的物体和接近的机器人不可避免地会产生巨大的冲击力,导致物体和机器人的接触不稳定和不可逆损伤。”我们提出了一个在线优化框架k:1)估计和预测物体的直线运动和角运动;2)通过序列二次规划选择物体每个表面的最佳接触位置以减轻碰撞;3)使用多模轨迹优化(MMTO)同时优化两个机器人的末端执行器运动、刚度和接触力。(4)在基于间接力控制的柔性机器人系统上实现碰撞感知的抓取运动。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Robotics. According to news reporting from Shenzhen, People's Republic of China, by NewsRx journalists, research stated, "This article investigates one of the m ost challenging tasks in dynamic manipulation-catching large-momentum moving obj ects. Beyond the realm of quasi-static manipulation, dealing with highly dynamic objects can significantly improve the robot's capability of interacting with it s surrounding environment." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news correspondents obtained a quote from the research from the Harbin Insti tute of Technology, "Yet, the inevitable motion mismatch between the fast moving object and the approaching robot will result in large impulsive forces, which l ead to the unstable contacts and irreversible damage to both the object and the robot. To address the above problems, we propose an online optimization framewor k to: 1) estimate and predict the linear and angular motion of the object, 2) se arch and select the optimal contact locations across every surface of the object to mitigate impact through sequential quadratic programming, 3) simultaneously optimize the end-effector motion, stiffness, and contact force for both robots u sing multimode trajectory optimization (MMTO), and 4) realise the impact-aware c atching motion on the compliant robotic system based on indirect force controlle r."
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