Not seeing is also believing: Combining object and metric spatial information

• Main Authors: Wong, Lawson L. S. (Contributor), Lozano-Perez, Tomas (Contributor), Kaelbling, Leslie P. (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2016-01-06T16:31:47Z.
• Subjects: Article
• Online Access: Get fulltext

 Spatial representations are fundamental to mobile robots operating in uncertain environments. Two frequently-used representations are occupancy grid maps, which only model metric information, and object-based world models, which only model object attributes. Many tasks represent space in just one of these two ways; however, because objects must be physically grounded in metric space, these two distinct layers of representation are fundamentally linked. We develop an approach that maintains these two sources of spatial information separately, and combines them on demand. We illustrate the utility and necessity of combining such information through applying our approach to a collection of motivating examples.