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Multi-Modal Robotic Learning, Reasoning and Planning.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multi-Modal Robotic Learning, Reasoning and Planning./
作者:	Gao, Feng.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
面頁冊數:	280 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-12, Section: B.
Contained By:	Dissertations Abstracts International83-12B.
標題:	Artificial intelligence. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29252284
ISBN:	9798819376249

Multi-Modal Robotic Learning, Reasoning and Planning.
Gao, Feng.

Multi-Modal Robotic Learning, Reasoning and Planning. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 280 p.

Source: Dissertations Abstracts International, Volume: 83-12, Section: B.

Thesis (Ph.D.)--University of California, Los Angeles, 2022.

This item must not be sold to any third party vendors.

Building an intelligent robot that is capable of collaborating with humans in daily tasks is a challenging problem. Although recent artificial intelligence research shows remarkable results in classical tasks, there is still a long way to achieve human-level intelligent robots. We need to start developing methods in terms of perception, learning, reasoning, and planning. In this dissertation, we study multi-modal robotic learning, reasoning, and planning from three different perspectives: (i) robot imitation learning: we first introduce a series of works including hardware prototype, data collection, modeling human demonstration, and planning for robot imitation learning. (ii) multi-modal reasoning: we study multi-modal reasoning in two different tasks. We develop a dataset and models for visual abstraction reasoning with human IQ test. Additionally, we propose a visual language reasoning method for outside knowledge visual question answering. (iii) robot planning: we show our attempts in robot planning. We introduce a physically realistic virtual testbed where robots can interact with humans. In addition, we show a hierarchical reinforcement learning method for robot planning.

ISBN: 9798819376249Subjects--Topical Terms:

516317
Artificial intelligence.
Subjects--Index Terms:

Artificial intelligence

Multi-Modal Robotic Learning, Reasoning and Planning.
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