Definition
Robot learning consists of a multitude of machine learning approaches, particularly reinforcement learning, inverse reinforcement learning, and regression methods, that have been adapted sufficiently to domain so that they allow learning in complex robot systems such as helicopters, flapping-wing flight, legged robots, anthropomorphic arms, and humanoid robots. While classical artificial intelligence-based robotics approaches have often attempted to manually generate a set of rules and models that allows the robot systems to sense and act in the real world, robot learning centers around the idea that it is unlikely that we can foresee all interesting real-world situations sufficiently accurate. Hence, the field of robot learning assumes that future robots need to be able to adapt to the real world, and domain-appropriate machine learning might offer the most approach in this direction.
Robot Learning Systems
As learning has found many backdoor entrances to robotics, this...
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Peters, J., Tedrake, R., Roy, N., Morimoto, J. (2017). Robot Learning. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_738
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_738
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