Abstract: This paper presents a novel algorithm for real-time path-planning in a dynamic environment such as a computer game. We utilize a real-time sampling approach based on the Rapidly Exploring Random Tree (RRT) algorithm that has enjoyed wide success in robotics. More specifically, our algorithm is based on the RRT* and informed RRT* variants. We contribute by introducing an online tree rewiring strategy that allows the tree root to move with the agent without discarding previously sampled paths. Our method also does not have to wait for the tree to be fully built, as tree expansion and taking actions are interleaved. To our knowledge, this is the first real-time variant of RRT*. We demonstrate our method, dubbed Real-Time RRT* (RT-RRT*), in navigating a maze with moving enemies that the controlled agent is required to avoid within a predefined radius. Our method finds paths to new targets considerably faster when compared to CL-RRT, a previously proposed real-time RRT variant.