Active, uncalibrated visual servoing

By B. Yoshimi, Peter K. Allen. 1994

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In Robotics & Control

Citations in the corpus

End-to-End Training of Deep Visuomotor Policies (2015, neutral): “Furthermore, our approach does not require any sort of camera calibration, in contrast to many visual servoing methods (though not all – see e.g. [11, 43]).”
Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection (2016, methodology): “, 2013), and several visual servoing methods have been proposed that do not directly require prior calibration between the robot and camera (Hosoda and Asada, 1994; Jägersand et al., 1997; Kragic and Christensen, 2002; Yoshimi and Allen, 1994).”
Deep spatial autoencoders for visuomotor learning (2015, neutral): “Furthermore, our approach does not require any sort of camera calibration, in contrast to many visual servoing methods (though not all – see e.g. [27], [28]).”
Zero-Shot Visual Imitation (2018, background): “Visual servoing is a standard problem in robotics (Koichi & Tom, 1993) that seeks to take actions that align the agent’s observation with a target configuration of carefully-designed visual features (Wilson et al., 1996; Yoshimi & Allen, 1994) or raw pixel intensities (Caron et al., 2013).”
Sim2Real View Invariant Visual Servoing by Recurrent Control (2017, unknown): “Several prior visual servoing methods also address servoing with uncalibrated cameras [36, 16, 21], but all of them address an “eyein-hand” setting, where the goal is to servo the camera toward a target view by using previously known geometric features and estimate the image Jacobian within an image”
Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control (2018, background): “Several prior visual servoing methods also address servoing with uncalibrated cameras [36, 16, 21], but all of them address an “eye-inhand” setting, where the goal is to servo the camera toward a target view by using previously known geometric features and estimate the image Jacobian within an image”
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation (2019, background): “…that can execute complex behaviours from only pixel inputs has been a well studied problem, for example with visual servoing (Mohta et al., 2014; Espiau et al., 1992; Wilson et al., 1996; Yoshimi & Allen, 1994; Jagersand et al., 1997; Lampe & Riedmiller, 2013; Sadeghi et al., 2018; Sadeghi, 2019).”
Visual servoing of an under-actuated dynamic rigid-body system: an image-based approach (2002, methodology): “Using centroid information is an old technique in visual servoing [2], [26], [15], [34].”
Uncalibrated visual servoing of robots using a depth-independent interaction matrix (2006, methodology): “For the eye-in-hand setup, Yoshimi and Allen [38] proposed an estimator of the image Jacobian for a peg-in-hole alignment task.”
Time Reversal as Self-Supervision (2018, background): “While some visual servoing methods work with uncalibrated camera inputs [9], [10], the general hand crafted nature of visual servoing limits the complexity of visual inputs and tasks where it can be applied.”
Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders (2015, result): “Furthermore, our approach does not require any sort of camera calibration, in contrast to many visual servoing methods (though not all – see e.g. [27], [28]).”
Experimental evaluation of uncalibrated visual servoing for precision manipulation (1997, methodology): “[1, 3, 2, 5, 6, 7, 11, 14, 13, 18, 19, 21 ] 1 ). Visual models suitable for specifying simple visual alignments have also been studied[22, 9, 8]. In [15] we show how to derive the robust visual servoing controllers used in this paper.”
A Practical Visual Servo Control for an Unmanned Aerial Vehicle (2008, methodology): “Using the centroid information is an old technique in visual servo control [2], [20], [33].”
Survey on Visual Servoing for Manipulation (2002, background): “(Yoshimi & Allen 1994b) present a system that uses snakes to simultaneously track the fingers of a robotic hand and a bolt in order to align the fingers with the bolt and unscrew it.”