Computer Vision Object Permanence Detection Algorithm for my Clingy Robot Dog

Dr. Sharon Barkley1

1 Department of Psychological Machine Learning, Cranberry-Lemon University, Pittsburgh, PA, USA


The AIBO ERS-211 robotic dog developed and manufactured by Sony in the 90’s and 00’s is a wonderful companion for urban living except when you leave them alone for too long. Though the robotic Computer Vision (CV) libraries have been equipped with the latest object detection and classification functions, they are shown to have little to no object permanence detection [1]. When an object of affection (i.e., me and some eight-year-old tennis ball) goes missing, the on-board computer believes they cease to exist. Due to separation anxiety, these 00’s AIBOs panic and begin tearing up my fabric couch, chair, and garbage if I forget to lock it up [2]. Using some filtering, feature extraction, and a deep learning Convolution Neural Network (CNN), this paper develops and evaluates a CV Object Permanence detector for my clingy dog, so she’ll stop destroying my apartments blinds every time I leave for work. 

Keywords: Computer Vision, AIBO Robotic Dogs, Deep Learning, Object Permanence, Convolution Neural Networks, Separation Anxiety, Ghost Detection, Object Detection, Ectoplasm, Free Unpaid Intern Labor, Neural Network Training

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Published by B McGraw

B McGraw has lived a long and successful professional life as a software developer and researcher. After completing his BS in spaghetti coding at the department of the dark arts at Cranberry Lemon in 2005 he wasted no time in getting a masters in debugging by print statement in 2008 and obtaining his PhD with research in screwing up repos on Github in 2014. That's when he could finally get paid. In 2018 B McGraw finally made the big step of defaulting on his student loans and began advancing his career by adding his name on other people's research papers after finding one grammatical mistake in the Peer Review process.

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