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Robust Behavior Cloning for Multi-Step Sequential Task Learning by Robots

مؤلف البحث
Mostafa Hussein
المشارك في البحث
تاريخ البحث
سنة البحث
2023
مجلة البحث
University of New Hampshire
موقع البحث
https://www.proquest.com/openview/b19d9efd698f4a371b1d52aa66a19202/1?pq-origsite=gscholar&cbl=18750&diss=y
ملخص البحث
This research is about learning high-level policies of multi-step sequential (MSS) tasks–such as activities of daily living–from demonstrations in a sample efficient manner. This research does not assume access to a simulator or an expert to provide more demonstrations. Learning a task policy in such a setting using state-of-the-art end-to-end approaches is sample inefficient due to a reliance on deep learning frameworks, which are known to require a large amount of data. Besides that, most imitation learning frameworks in robotics assume that a domain expert’s demonstration always contains a correct way of doing the task. Despite its theoretical convenience, this assumption has limited practical value in real-world imitation learning. There are many reasons for an expert in the real world to provide demonstrations that may contain incorrect or potentially unsafe ways of doing a task. To that end, my work proposes a …