In this work, we propose a gesture based language to allow humans to interact with robots using their body in a natural way. We have created a new gesture detection model using neural networks and a custom dataset of humans performing a set of body gestures to train our network. Furthermore, we compare body gesture communication with other communication channels to acknowledge the importance of adding this knowledge to robots. The presented approach is extensively validated in diverse simulations and real-life experiments with non-trained volunteers. This attains remarkable results and shows that it is a valuable framework for social robotics applications, such as human robot collaboration or human-robot interaction.
翻译:在这项工作中,我们建议一种基于手势的语言,使人类能够自然地利用机器人的身体与机器人进行互动。我们创建了一种新的手势检测模型,使用神经网络和一套用于训练我们网络的人体手势的定制数据集。此外,我们将身体手势交流与其他通信渠道进行比较,以承认将这种知识添加到机器人中的重要性。所提出的方法在与未经训练的志愿者进行的各种模拟和现实生活中实验中得到了广泛的验证。这取得了显著的成果,并表明它是社会机器人应用的宝贵框架,例如人类机器人协作或人类机器人互动。