论文标题
通过行动识别和增强层次二次编程的社交和符合人体工程学的人类机器人合作
Sociable and Ergonomic Human-Robot Collaboration through Action Recognition and Augmented Hierarchical Quadratic Programming
论文作者
论文摘要
认识人类所采取的行动以及对其意图的预期是重要的推动力，可以在人类机器人团队中产生社交和成功的合作。同时，机器人应具有由协作任务或人类引起的多种目标和约束的能力。在这方面，我们提出了视力技术来执行人类的行动识别和图像分类，这些技术被整合到增强的层次二次编程（AHQP）方案中，以层次优化机器人的反应性行为和人类的人体工程学。所提出的框架允许执行任务时，可以直观地在空间中命令机器人。该实验证实了人体工程学和可用性的增加，这是减少肌肉骨骼疾病并增加自动化信任的基本参数。
The recognition of actions performed by humans and the anticipation of their intentions are important enablers to yield sociable and successful collaboration in human-robot teams. Meanwhile, robots should have the capacity to deal with multiple objectives and constraints, arising from the collaborative task or the human. In this regard, we propose vision techniques to perform human action recognition and image classification, which are integrated into an Augmented Hierarchical Quadratic Programming (AHQP) scheme to hierarchically optimize the robot's reactive behavior and human ergonomics. The proposed framework allows one to intuitively command the robot in space while a task is being executed. The experiments confirm increased human ergonomics and usability, which are fundamental parameters for reducing musculoskeletal diseases and increasing trust in automation.
