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KnowledgeBot: Improving assistive robot for task completion and live interaction via neuro-symbolic reasoning

By Virginia Tech
2023
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As artificial intelligence continues to advance, the development of intelligent assistive agents that can help people in completing daily tasks has become an area of increasing interest. However, the automation of such agents presents several challenges: (1) the enormous variety of user-defined tasks, (2) the ability of complex reasoning and visual comprehension for carrying out actions, and (3) natural interaction with humans. In this paper, we introduce KnowledgeBot, a conversational embodied agent designed to address these challenges. KnowledgeBot is designed for the Alexa Prize SimBot Challenge. The primary goal of this agent is to accomplish various tasks effectively by interacting with users while ensuring an optimal user experience. To achieve this, KnowledgeBot processes user instructions and environmental perceptions correspondingly take actions and respond to users through a series of components, including symbolic reasoning and neural-based action planning and prediction modules, vision models for semantic segmentation and visual grounding, as well as a situated dialogue module. By integrating these components, our agent is capable of carrying out a variety of tasks interactively with users in a natural and conversational manner. We demonstrate the effectiveness of our approach by evaluating our approach on TEACh and Arena instruction following datasets.

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