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Reinforcement Learning Trajectory Generation and Control for Aggressive Perching on Vertical Walls with Quadrotors
This paper proposes a trajectory generating and tracking method for quadrotor perching that takes the advantages of reinforcement learning controller and traditional controller.
Robotics Systems and Control Systems and Control
Towards Combining On-Off-Policy Methods for Real-World Applications
In this paper, we point out a fundamental property of the objective in reinforcement learning, with which we can reformulate the policy gradient objective into a perceptron-like loss function, removing the need to distinguish between on and off policy training.
