2021 IEEE International Conference on Robotics and Automation (ICRA) 2021
DOI: 10.1109/icra48506.2021.9560862
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Residual Model Learning for Microrobot Control

Abstract: A majority of microrobots are constructed using compliant materials that are difficult to model analytically, limiting the utility of traditional model-based controllers. Challenges in data collection on microrobots and large errors between simulated models and real robots make current model-based learning and sim-to-real transfer methods difficult to apply. We propose a novel framework residual model learning (RML) that leverages approximate models to substantially reduce the sample complexity associated with… Show more

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“…This simplification will be an obstacle when considering a robotic food arrangement. We might need a better solution, e.g., a better physical simulator and an approximation method of foods [24]. Next, a cost function and map corresponding to w must be implemented by interpreting the rules, which is tedious.…”
Section: Discussionmentioning
confidence: 99%
“…This simplification will be an obstacle when considering a robotic food arrangement. We might need a better solution, e.g., a better physical simulator and an approximation method of foods [24]. Next, a cost function and map corresponding to w must be implemented by interpreting the rules, which is tedious.…”
Section: Discussionmentioning
confidence: 99%