Nowadays, robots are found in a growing number of areas where they collaborate closely with humans. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, supporting people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior, which is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their motion intention and comprehending how they "think" about their actions. Moreover, other information sources often occupy human visual and audio modalities, rendering them frequently unsuitable for transmitting such information. We work on a solution that communicates cobot intention via haptic feedback to tackle this challenge. In our concept, we map planned motions of the cobot to different haptic patterns to extend the visual intention feedback.

翻译：如今，机器人在越来越多与人类密切协作的领域中得到应用。凭借轻量化材料和安全传感器，这些协作机器人在家庭护理领域日益普及，能够帮助行动障碍者处理日常生活事务。然而，当协作机器人自主执行动作时，人类协作者仍难以理解和预测其行为——这一能力对建立信任与用户接受度至关重要。预测协作机器人行为的一个关键方面，在于理解它们的运动意图以及它们如何"思考"自身动作。此外，人类的视觉和听觉通道常被其他信息源占用，导致这些通道不适于传递此类信息。为应对这一挑战，我们提出一种通过触觉反馈传递协作机器人意图的解决方案。在我们的概念中，通过将协作机器人规划的运动映射至不同触觉模式，可扩展原有的视觉意图反馈。