Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis [PDF]
Frontiers in Robotics and AIImitation learning (IL), a burgeoning frontier in machine learning, holds immense promise across diverse domains. In recent years, its integration into robotics has sparked significant interest, offering substantial advancements in autonomous control ...
Siavash Mahmoudi +8 more
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Interactive imitation learning for dexterous robotic manipulation: challenges and perspectives—a survey [PDF]
Frontiers in Robotics and AIDexterous manipulation is a crucial yet highly complex challenge in humanoid robotics, demanding precise, adaptable, and sample-efficient learning methods. As humanoid robots are usually designed to operate in human-centric environments and interact with
Edgar Welte, Rania Rayyes
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Visual imitation learning from one-shot demonstration for multi-step robot pick and place tasks [PDF]
Scientific ReportsImitation learning provides an intuitive approach for robot programming by enabling robots to learn directly from human demonstrations. While recent visual imitation learning methods have shown promise, they often depend on large datasets, which limits ...
Shuang Lu +2 more
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Anti-Jamming Communication Using Imitation Learning [PDF]
Entropy, 2023 The communication reliability of wireless communication systems is threatened by malicious jammers. Aiming at the problem of reliable communication under malicious jamming, a large number of schemes have been proposed to mitigate the effects of malicious
Zhanyang Zhou +3 more
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Dataset for the assessment of presence and performance in an augmented reality environment for motor imitation learning: A case-study on violinists. [PDF]
Data Brief, 2023 Campo A +3 more
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Domain Adaptation for Imitation Learning Using Generative Adversarial Network [PDF]
Sensors, 2021 Imitation learning is an effective approach for an autonomous agent to learn control policies when an explicit reward function is unavailable, using demonstrations provided from an expert.
Tho Nguyen Duc +3 more
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An Adaptive Imitation Learning Framework for Robotic Complex Contact-Rich Insertion Tasks. [PDF]
Front Robot AI, 2021 Wang Y +3 more
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Neuroprosthetic Decoder Training as Imitation Learning. [PDF]
PLoS Comput Biol, 2016 Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task.
Merel J +3 more
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ACM Computing Surveys, 2017 Imitation learning techniques aim to mimic human behavior in a given task. An agent (a learning machine) is trained to perform a task from demonstrations by learning a mapping between observations and actions. The idea of teaching by imitation has been around for many years; however, the field is gaining attention recently due to advances in computing ...
Ahmed Hussein +3 more
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Co-imitation: Learning Design and Behaviour by Imitation
Proceedings of the AAAI Conference on Artificial Intelligence, 2023 The co-adaptation of robots has been a long-standing research endeavour with the goal of adapting both body and behaviour of a robot for a given task, inspired by the natural evolution of animals. Co-adaptation has the potential to eliminate costly manual hardware engineering as well as improve the performance of systems.
Rajani, Chang +4 more
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