Curiosity is widely recognized as a fundamental mode of cognition and is particularly critical during childhood development. As such, it drives children and adults alike towards novel, previously unseen objects, movements and other stimuli, yielding new information and insights about the world and its underlying processes. Developing intelligent robots with a sense of ”curiosity” may lead to an important breakthrough in artificial intelligence: agents that proactively expand their knowledge and capabilities by themselves through a snowballing process of information-generation. Instead of programming or demonstrating behavior, a robot child could learn about itself and its environment through playful, curious interactions. Recent attempts in using curiosity-inspired approaches in robot learning, computer vision, task and motion planning, human-robot interaction and other fields, have generated remarkable results but are largely independent of each other. Hence, there is an increasing need for a better understanding of this phenomenon at a broader scale through the collaboration of a diverse set of researchers. In this workshop, we aim to bring together researchers, students and practitioners to discuss how to build curious robots. Leading experts on the topic of algorithmic and biological curiosity will present their current state-of-the-art research and discuss ongoing work and critical outstanding challenges.