The recent advancements in autonomy algorithms and computational hardware have enabled robots to break out of contrived laboratory settings and be deployed in the real world. There is a growing demand for modern civilian and military systems to not only exhibit complex and intelligent behavior in response to external stimuli, but to augment capabilities through machine learning techniques. In order for complex robotic systems to demonstrate intelligent and consistent performance across diverse scenarios that they encounter, it's imperative that a number of distinct, yet interrelated modules (i.e. estimation, decision making, learning, control) are tightly integrated. Today, these individual topics are being widely researched upon in isolation. Hence, this workshop aims to bring together researchers from different communities and discuss problems that occur at the intersection of their fields, present recent advances and contemplate on future directions of research.