Continual Learning of Visual Concepts for Robots through Limited Supervision

• URL: http://arxiv.org/abs/2101.10509v1
• Date: Tue, 26 Jan 2021 01:26:07 GMT
• Title: Continual Learning of Visual Concepts for Robots through Limited Supervision
• Authors: Ali Ayub, Alan R. Wagner
• Abstract summary: My research focuses on developing robots that continually learn in dynamic unseen environments/scenarios. I develop machine learning models that produce State-of-the-results on benchmark datasets.
• Score: 9.89901717499058
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: For many real-world robotics applications, robots need to continually adapt and learn new concepts. Further, robots need to learn through limited data because of scarcity of labeled data in the real-world environments. To this end, my research focuses on developing robots that continually learn in dynamic unseen environments/scenarios, learn from limited human supervision, remember previously learned knowledge and use that knowledge to learn new concepts. I develop machine learning models that not only produce State-of-the-results on benchmark datasets but also allow robots to learn new objects and scenes in unconstrained environments which lead to a variety of novel robotics applications.

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