用参数化技能系统实现人-机器人-吊车协同作业的高效编程与执行
Programming and execution of skill-based human-robot-crane collaborative tasks
- 基于CAD模型的参数化技能编程，支持灵活任务配置
- 采用事件驱动的动态行为树控制结构，提升执行鲁棒性
- 适用于需要高灵活性与协作精度的工业制造与物流场景
日益多变的生产需求给机器人制造和室内物流带来挑战，亟需提升敏捷性、灵活性与鲁棒性。机器人技能通过整合运动、工具操作与传感器感知，为参数可变的任务集提供统一执行机制。本文展示了一种基于CAD模型的易用编程与执行系统，支持参数化技能及技能监控。执行控制结构为动态且可参数化的，基于改进的行为树（Behavior Tree），仅使用事件驱动通信。以人-机器人-吊车协同任务为例：操作员指导悬挂起重机与机械臂，将重物在吊车支撑下由机械臂引导，精准插入目标位置。
原文摘要 · Abstract (English)
Highly varying production sets increasing challenges for robotic manufacturing and indoor logistics. New capabilities for agility, flexibility, and robustness are needed. Robot skills, integrating motions, tool operations, and sensor perceptions consistently provide an execution mechanism for a versatile set of tasks with varying parameters. In this paper, easy-to-use CAD-model based programming and execution system for parametrized skills and skill monitors is showcased. The execution control structure is dynamic and parametrized, based on a modified Behavior Tree, where only event based communication is used. A human-robot-crane collaborative skill is shown as a test example, where a human instructs an overhead crane and a manipulator in inserting a heavy object supported by the crane, and guided by the manipulator, into the goal.
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