Co-robots refer to a class of robots that are collaborative in nature and learn from humans and their environments and in turn, enable humans to learn from them. In order for co-robots to learn and interact with humans and their environment, they must first be able to i) sense their environment and ii) navigate around their environment. The objective of this work is to explore the feasibility of co-robots learning how to navigate their environment, by observing the body movement patterns of their human counterparts. The co-robot introduced in this work is designed using Commercial, Off-The-Shelf (COTS) sensing systems such as the Microsoft Kinect. Knowledge gained from this work will inform decisions makers seeking to employ co-robots in manufacturing settings that involve human-robot interactions. A case study involving Pennie the co-robot is used to validate the proposed methodology.