Appearance-Based Obstacle Detection with Monocular Color Vision

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Map-Based Precision Vehicle Localization in Urban Environments (2007, background): “The variable ǫt is a Gaussian noise variable with zero mean and covariance Rt. Vehicle dynamics are discussed in detail in [15].”
Learning Visual Object Categories for Robot Affordance Prediction (2010, background): “Ulrich and Nourbakhsh (2000) describes an on-line learning method for indoor robot navigation based on color modeling and stereo sensing.”
Robot Programming by Demonstration (2010, methodology): “In [13], depth cues are obtained from monocular images and genetic programming is used to find obstacle avoidance algorithms and in [ 24 ], the authors propose color histograms to model the appearance of the floor obtained from a trapezoidal reference area using a single monocular camera.”
Introduction to Autonomous Mobile Robots (2004, background): “48 shows an appearance-based floor plane extraction algorithm operating on both indoor and outdoor images [151].”