Humans use continuous visual feedback from the hand to control fast reaching movements

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Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection (2016, background): “Even complex manipulation tasks, such as extracting a single object from a cluttered bin, can be performed without first localizing the objects or mapping the scene, relying instead on continuous sensing from touch and vision (Johannson and Flanagan, 2007; Saunders and Knill, 2003).”
Error correction, sensory prediction, and adaptation in motor control. (2010, background): “…responses to perturbations are often much larger in amplitude than their short-latency counterparts (Strick, 1978), and response to visual and proprioceptive error are salient throughout the entire course of even relatively quick arm movements (Saunders and Knill, 2003;Saunders and Knill, 2004).”
Visual Feedback Control of Hand Movements (2004, methodology): “Although the role of visual feedback from the hand for guiding movements has been the focus of extensive work (Keele and Posner, 1968; Carlton, 1981; Connolly and Goodale, 1999; Saunders and Knill, 2003), previous studies have addressed only basic issues of whether visual feedback contributes at var”
A theory for how sensorimotor skills are learned and retained in noisy and nonstationary neural circuits (2013, background): “This assumption is supported by findings that precise movements require online visual (23) and proprioceptive (24) feedback.”