Common Sense Data Acquisition for Indoor Mobile Robots

Common sense knowledge can be efficiently collected from non-experts over the web in a similar fashion to the Open Mind family of distributed knowledge capture projects. We describe the collection of common sense data through the Open Mind Indoor Common Sense (OMICS) website. We restrict the domain to indoor home and office environments to obtain dense knowledge. The knowledge was collected through sentence templates that were generated dynamically based on previous user input. Entries were converted into relations and saved into a database. We discuss the results of this online collaborative effort and describe two applications of the collected data to indoor mobile robots. We discuss active desire selection based on current beliefs and commands and a room-labeling application based on probability estimates from the common sense knowledge base.

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