Obstacle Avoidance and Navigation Utilizing Reinforcement Learning with Reward Shaping

28 Mar 2020 Daniel Zhang Colleen P. Bailey

In this paper, we investigate the obstacle avoidance and navigation problem in the robotic control area. For solving such a problem, we propose revised Deep Deterministic Policy Gradient (DDPG) and Proximal Policy Optimization algorithms with an improved reward shaping technique... (read more)

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Methods used in the Paper


METHOD TYPE
Experience Replay
Replay Memory
Entropy Regularization
Regularization
Dense Connections
Feedforward Networks
Weight Decay
Regularization
ReLU
Activation Functions
Adam
Stochastic Optimization
Convolution
Convolutions
Batch Normalization
Normalization
DDPG
Policy Gradient Methods
PPO
Policy Gradient Methods