Search Results for author: Siyu Dai

Found 3 papers, 0 papers with code

Automatic Curricula via Expert Demonstrations

no code implementations16 Jun 2021 Siyu Dai, Andreas Hofmann, Brian Williams

We propose Automatic Curricula via Expert Demonstrations (ACED), a reinforcement learning (RL) approach that combines the ideas of imitation learning and curriculum learning in order to solve challenging robotic manipulation tasks with sparse reward functions.

Imitation Learning Reinforcement Learning (RL)

Fast-reactive probabilistic motion planning for high-dimensional robots

no code implementations3 Dec 2020 Siyu Dai, Andreas Hofmann, Brian C. Williams

Many real-world robotic operations that involve high-dimensional humanoid robots require fast-reaction to plan disturbances and probabilistic guarantees over collision risks, whereas most probabilistic motion planning approaches developed for car-like robots can not be directly applied to high-dimensional robots.

Collision Avoidance Motion Planning +1

An Empowerment-based Solution to Robotic Manipulation Tasks with Sparse Rewards

no code implementations15 Oct 2020 Siyu Dai, Wei Xu, Andreas Hofmann, Brian Williams

In order to provide adaptive and user-friendly solutions to robotic manipulation, it is important that the agent can learn to accomplish tasks even if they are only provided with very sparse instruction signals.

reinforcement-learning Reinforcement Learning (RL)

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