Data-Efficient Model Learning and Prediction for Contact-Rich Manipulation Tasks

IEEE Robotics and Automation Letters(2020)

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摘要
In this letter, we investigate learning forward dynamics models and multi-step prediction of state variables (long-term prediction) for contact-rich manipulation. The problems are formulated in the context of model-based reinforcement learning (MBRL). We focus on two aspects-discontinuous dynamics and data-efficiency-both of which are important in the identified scope and pose significant challeng...
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关键词
Predictive models,Uncertainty,Task analysis,Manipulator dynamics,Probabilistic logic
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