Tuesday, February 10, 2015

Motion prediction

I just thought up this experiment a couple of minutes ago:

I'm a casual juggler and I'm wondering whether, when I juggle, I'm predicting the parabolic path of the balls as they fall through the air or I'm doing something else, like predicting a linear continuation of the balls' motion from any given point. To test this, I would have myself standing or sitting with my head in a fixed position. I would have a machine for throwing balls in a predictable arc (e.g., a batting cage ball delivery system). I would have the balls thrown with a spread of trajectories that land within the range of my arms for catching. I would have a head-mounted camera recording approximately the visuals that I could see. I would have a set of goggles that could obscure my vision after a specific time-delay from launching the balls. Each trial would consist of the throwing machine throwing a ball and myself attempting to catch. To establish a baseline, I would attempt to catch the balls without my vision being obscured at any point in the ball's arc. Then, I would have my vision obscured before the top of the arc, at the top, and after the top until the next trial. I would have an assistant record the trials on which I caught the ball and the ones on which I did not.

In order to reject the theory that I was calculating parabolic arcs, my performance when my vision was obscured would have to be close to as-good-as my performance when it was not. We would still expect that when my vision was blocked earlier, my performance would be worse than later. The camera recordings are to explore whether an alternate strategy, linear extrapolation, could be in effect. For the failed trials, we would predict the linear path of the ball from the time, maybe .1s, before my vision was obscured and see if my hand placement was closer to intersecting that path than the parabolic.

Since I thought of this experiment before consulting any of the literature, I'm going to do a little study. I'm starting with these here:

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