@incollection{Kontoudis2022RRTQX,
	title={RRT-QX: Real-Time Kinodynamic Motion Planning in Dynamic Environments with Continuous-Time Reinforcement Learning},
	author={Kontoudis, George P and Vamvoudakis, Kyriakos G and Xu, Zirui},
	editor      = {Wei, Bin},
	booktitle   = {Brain and Cognitive Intelligence: Control in Robotics},
	publisher   = {Taylor \& Francis Group, CRC Press},
	abstract = {This chapter presents a real-time kinodynamic motion planning technique for linear systems with completely unknown dynamics in environments with unpredictable obstacles. The methodology incorporates: i) a sampling-based algorithm for path planning and fast replanning; and ii) continuous-time Q-learning for the solution of finite-horizon optimal control problems in real-time. The path planner produces a set of waypoints that dynamically change in time according to the unpredictably appearing obstacles, while the Q-learning controller is responsible for optimal waypoint navigation. The efficacy of the methodology has been validated with simulations. },
	year={2022},
	keywords={motion planning, reinforcement learning, optimal control},
	url_pdf = {Chap22_Kontoudis_RRTQX_RealTimeKinodynamicMotionPlanningDynamicEnvironments.pdf},
	url_video = {https://youtu.be/Sxu04gSdsEA},
	doi = {10.1201/9781003050315-1}
}

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