Paper
29 May 2013 Primate-inspired vehicle navigation using optic flow and mental rotations
Ronald C. Arkin, Frank Dellaert, Natesh Srinivasan, Ryan Kerwin
Author Affiliations +
Abstract
Robot navigation already has many relatively efficient solutions: reactive control, simultaneous localization and mapping (SLAM), Rapidly-Exploring Random Trees (RRTs), etc. But many primates possess an additional inherent spatial reasoning capability: mental rotation. Our research addresses the question of what role, if any, mental rotations can play in enhancing existing robot navigational capabilities. To answer this question we explore the use of optical flow as a basis for extracting abstract representations of the world, comparing these representations with a goal state of similar format and then iteratively providing a control signal to a robot to allow it to move in a direction consistent with achieving that goal state. We study a range of transformation methods to implement the mental rotation component of the architecture, including correlation and matching based on cognitive studies. We also include a discussion of how mental rotations may play a key role in understanding spatial advice giving, particularly from other members of the species, whether in map-based format, gestures, or other means of communication. Results to date are presented on our robotic platform.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ronald C. Arkin, Frank Dellaert, Natesh Srinivasan, and Ryan Kerwin "Primate-inspired vehicle navigation using optic flow and mental rotations", Proc. SPIE 8756, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2013, 87560M (29 May 2013); https://doi.org/10.1117/12.2018920
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Cited by 1 scholarly publication.
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KEYWORDS
Optical flow

Cameras

Expectation maximization algorithms

Motion estimation

Motion models

Robotics

Target detection

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