NRI: FND: Safe and Efficient Robot Collaboration System (SERoCS) for Next Generation Intelligent Industrial Co-Robots

NRI：FND：用于下一代智能工业协作机器人的安全高效的机器人协作系统（SERoCS）

• 批准号: 1734109
• 负责人: Masayoshi Tomizuka
• 金额: $ 75万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734109&HistoricalAwards=false
• 关键词: NRI; FND; Safe; Efficient; Robot

In current automated factories, humans and robots typically work separately, partly for safety reasons and partly because full robotic automation has been a goal. In recent years, however, it has been recognized that there are tremendous opportunities when robots are brought out of their cages and allowed to collaborate with human workers in a shared workspace. Such collaboration takes advantage of both the intelligence, adaptability and flexibility of humans and the endurance, strength and reliability of robots. In any collaboration between humans and robots, i.e. co-robots, it is important to consider and ensure both the safety of the humans and the best performance of the robots. This project aims to establish a set of design principles for a safe and efficient robot collaboration system (SERoCS). Outside of factories, SERoCS may be applied in other settings, such as with mobility assistance of humans by robots and automated driving situations where human-driven vehicles and autonomous vehicles share the same road.SERoCS consists of three parts: (1) robust cognition algorithms for environment monitoring, (2) optimal task planning algorithms for safe human-robot collaboration, and (3) safe motion planning and control algorithms for safe human-robot interactions (HRI). Research on cognition environment monitoring algorithms involves the construction of a cognition model library and the implementation of an algorithm for online prediction and adaptation of human behavior. In addition, task planning algorithms for safe human-robot collaboration require the construction of a motion skill library learned from human demonstrations and its association with an algorithm for online task planning and objective generation using learned skills. The two-layer structure that will be employed for safe motion planning and control algorithms comprises a long-term, efficiency-oriented planning layer and a short-term, safety-oriented control layer for safe HRIs. The SERoCS will signicantly expand the skill sets of the co-robots and prevent and minimize occurrences of human-robot collision and robot-robot collision during operation.

在目前的自动化工厂中，人类和机器人通常分开工作，部分原因是安全原因，部分原因是完全的机器人自动化一直是一个目标。然而，近年来，人们认识到，当机器人被带出笼子并允许在共享工作空间中与人类工人合作时，会带来巨大的机会。 这种协作既利用了人类的智能、适应性和灵活性，又利用了机器人的耐力、力量和可靠性。在人类和机器人之间的任何协作中，重要的是要考虑并确保人类的安全和机器人的最佳性能。本计画旨在建立一套安全且有效率的机器人合作系统（SERoCS）的设计原则。 在工厂之外，SERoCS可以应用于其他环境，例如机器人对人类的移动辅助以及人类驾驶车辆和自动驾驶车辆共享同一条道路的自动驾驶情况。SERoCS由三部分组成：（1）用于环境监测的鲁棒认知算法，（2）用于安全人机协作的最优任务规划算法，以及（3）用于安全人机交互（HRI）的安全运动规划和控制算法。 认知环境监测算法的研究包括认知模型库的构建和行为在线预测与自适应算法的实现。此外，用于安全的人机协作的任务规划算法需要构建从人类演示中学习的运动技能库，并将其与用于在线任务规划和使用学习到的技能生成目标的算法相关联。将用于安全运动规划和控制算法的两层结构包括用于安全HRI的长期、效率导向的规划层和短期、安全导向的控制层。SERoCS将显著扩展协作机器人的技能集，并防止和最大限度地减少操作过程中人机碰撞和机器人碰撞的发生。

项目成果

Fast Robot Motion Planning with Collision Avoidance and Temporal Optimization

具有碰撞避免和时间优化的快速机器人运动规划

• DOI: 10.1109/icarcv.2018.8581194
• 发表时间: 2018
• 期刊: Robotics and Vision (ICARCV
• 作者: Lin, Hsien-Chung;Liu, Changliu;Tomizuka, Masayoshi
• 通讯作者: Tomizuka, Masayoshi

Long-Term Trajectory Prediction of the Human Hand and Duration Estimation of the Human Action

人手的长期轨迹预测和人类动作的持续时间估计

• DOI: 10.1109/lra.2021.3124524
• 发表时间: 2022
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Cheng, Yujiao;Tomizuka, Masayoshi
• 通讯作者: Tomizuka, Masayoshi

A Framework for Robot Grasp Transferring with Non-rigid Transformation

非刚性变换机器人抓取转移框架

• DOI: 10.1109/iros.2018.8593668
• 发表时间: 2019
• 期刊: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS
• 作者: Lin, Hsien-Chung;Tang, Te;Fan, Yongxiang;Tomizuka, Masayoshi
• 通讯作者: Tomizuka, Masayoshi

Safe Control Algorithms Using Energy Functions: A Uni ed Framework, Benchmark, and New Directions

使用能量函数的安全控制算法：统一框架、基准和新方向

• DOI: 10.1109/cdc40024.2019.9029720
• 发表时间: 2019
• 期刊: 2019 IEEE 58th Conference on Decision and Control (CDC
• 作者: Wei, Tianhao;Liu, Changliu
• 通讯作者: Liu, Changliu

Experimental Evaluation of Human Motion Prediction Toward Safe and Efficient Human Robot Collaboration

人体运动预测对安全高效人机协作的实验评估

• DOI: 10.23919/acc45564.2020.9147277
• 发表时间: 2020
• 期刊: Experimental Evaluation of Human Motion Prediction Toward Safe and Efficient Human Robot Collaboration
• 作者: Zhao, Weiye;Sun, Liting;Liu, Changliu;Tomizuka, Masayoshi
• 通讯作者: Tomizuka, Masayoshi