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，机器人在与人类紧密协作的领域日益增多。得益于轻质材料和安全传感器，这类协作机器人在家庭护理中越来越受欢迎，能够支持身体障碍者的日常生活。然而，当协作机器人自主执行动作时，人类协作者理解和预测其行为仍具挑战性——这对建立信任和用户接受度至关重要。预测协作机器人行为的关键之一在于理解其运动意图，以及它们如何"思考"自身动作。此外，其他信息源常占用人类的视觉和听觉通道，导致这些通道不适合传输此类信息。我们提出通过触觉反馈传递协作机器人意图的解决方案来应对这一挑战。在我们的概念中，将协作机器人的计划运动映射为不同的触觉模式，以扩展视觉意图反馈。