An important window into sensorimotor function is how humans interact and stop moving projectiles, such as stopping a door from closing shut or catching a ball. Previous studies have suggested that humans time the initiation and modulate the amplitude of their muscle activity based on the momentum of the approaching object. However, real-world experiments are constrained by laws of mechanics, which cannot be manipulated experimentally to probe the mechanisms of sensorimotor control and learning. An augmented-reality variant of such tasks allows for experimental manipulation of the relationship between motion and force to obtain novel insights into how the nervous system prepares motor responses to interact with moving stimuli. Existing paradigms for studying interactions with moving projectiles use massless objects and are primarily focused on quantifying gaze and hand kinematics. Here, we developed a novel collision paradigm using a robotic manipulandum where participants mechanically stopped a virtual object moving in the horizontal plane. On each block of trials, we varied the virtual object's momentum by increasing either its velocity or mass. Participants stopped the object by applying a force impulse that matched the object momentum. We observed that hand force increased as a function of object momentum linked to changes in virtual mass or velocity, similar to results from studies involving catching free-falling objects. In addition, increasing object velocity resulted in later onset of hand force relative to the impending time-to-contact. These findings show that the present paradigm can be used to determine how humans process projectile motion for hand motor control.