Robot Learning and Adaptation for Intelligent Behavior

This work will offer an overview of the function that machine learning plays in field robotics. The relevance enabling robots to acquire knowledge via experience and adjust their behaviour response new situations is underlined. allows adapt surroundings become more efficient. article delves further into a number different approaches learning, such as reinforcement imitation deep learning. These are particularly well-suited for use robots. Some modern approaches, meta-learning, Bayesian optimisation, domain randomization, adversarial training, presented here. final section paper discusses topic future robotics, focusing on possibility may powerful capable future, eventually taking over jobs either too dangerous or time-consuming people manage.