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PrepTurn: An anticipatory turning reinforcement learning framework for fast sequential quadruped navigation

PrepTurn is a reinforcement learning framework for anticipatory maneuvering in continuous local navigation. It maps the current and next pose goals directly to joint actions, letting the upcoming goal influence how the robot approaches the current one. The framework uses a persistent-credit reward to encourage completing the entire goal sequence while in motion, and an automatic curriculum that gradually increases goal difficulty to stabilize turning behavior; simulation and onboard Unitree Go2 experiments show high sequential traversal completion rates and reduced stop-and-go motion.

Part of the event: PrepTurn: A Reinforcement Learning Framework for Anticipatory Turning in Quadruped Robots

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