RRT-QX: Real-Time Kinodynamic Motion Planning in Dynamic Environments with Continuous-Time Reinforcement Learning. Kontoudis, G. P, Vamvoudakis, K. G, & Xu, Z. In Brain and Cognitive Intelligence: Control in Robotics. Taylor & Francis Group, CRC Press, 2022.
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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.

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