Visual Homing From Scale With an Uncalibrated Omnidirectional Camera

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A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation (2016, neutral): “uracy of the sensor and the controller of the manipulator. Visual-feedback control loop increases the overall accuracy of the system. Now it is widely used in mobile robot control (Fang et al., 2012; Liu et al., 2013a), UAV control (Lee et al., 2012), target tracking (Cr´etual and Chaumette, 2001a; ”
A deep-network solution towards model-less obstacle avoidance (2016, background): “A series of tasks, such as visual localization[19], visual homing [20], [21], exploration and path-following[22], could be achieved.”
Deep-learning in Mobile Robotics - from Perception to Control Systems: A Survey on Why and Why not (2016, methodology): “As a basic and low-cost navigation ability, traditionally the homing vector was motivated by visual servoing algorithms (Liu et al., 2010, 2012, 2013).”
Image Matching from Handcrafted to Deep Features: A Survey (2020, methodology): “In this category, the homing vector can be determined by transforming the correspondences into motion flows (Ma et al. 2018b; Churchill and Vardy 2013; Liu et al. 2013; Zhao and Ma 2017).”