Natural language is an effective tool for communication, as information can be expressed in different ways and at different levels of complexity. Verbal commands, utilized for instructing robot tasks, can therefor replace traditional robot programming techniques, and provide a more expressive means to assign actions and enable collaboration. However, the challenge of utilizing speech for robot programming is how actions and targets can be grounded to physical entities in the world. In addition, to be time-efficient, a balance needs to be found between fine- and course-grained commands and natural language phrases. In this work we provide a framework for instructing tasks to robots by verbal commands. The framework includes functionalities for single commands to actions and targets, as well as longer-term sequences of actions, thereby providing a hierarchical structure to the robot tasks. Experimental evaluation demonstrates the functionalities of the framework by human collaboration with a robot in different tasks, with different levels of complexity. The tools are provided open-source at https://petim44.github.io/voice-jogger/

翻译：自然语言是一种有效的沟通工具，信息可以以不同方式和不同复杂程度表达。用于指导机器人任务的口头指令因此可以取代传统的机器人编程技术，并提供更富有表现力的方式来分配动作并实现协作。然而，利用语音进行机器人编程的挑战在于如何将动作和目标与真实世界中的物理实体相联系。此外，为了提高时间效率，需要在精细与粗略指令及自然语言短语之间找到平衡。在本工作中，我们提出了一个通过口头指令向机器人下达任务的框架。该框架包括从单一指令到动作和目标的功能，以及更长期的动作序列，从而为机器人任务提供层级结构。实验评估通过人与机器人在不同复杂程度任务中的协作，展示了该框架的功能。该工具已在https://petim44.github.io/voice-jogger/上开源提供。