Crash Prediction Using Deep Learning in a Disorienting Spaceflight Analog Balancing Task

Author:

Wang Yonglin,Tang Jie,Vimal Vivekanand Pandey,Lackner James R.,DiZio Paul,Hong Pengyu

Abstract

Were astronauts forced to land on the surface of Mars using manual control of their vehicle, they would not have familiar gravitational cues because Mars’ gravity is only 0.38 g. They could become susceptible to spatial disorientation, potentially causing mission ending crashes. In our earlier studies, we secured blindfolded participants into a Multi-Axis Rotation System (MARS) device that was programmed to behave like an inverted pendulum. Participants used a joystick to stabilize around the balance point. We created a spaceflight analog condition by having participants dynamically balance in the horizontal roll plane, where they did not tilt relative to the gravitational vertical and therefore could not use gravitational cues to determine their position. We found 90% of participants in our spaceflight analog condition reported spatial disorientation and all of them showed it in their data. There was a high rate of crashing into boundaries that were set at ± 60° from the balance point. Our goal was to see whether we could use deep learning to predict the occurrence of crashes before they happened. We used stacked gated recurrent units (GRU) to predict crash events 800 ms in advance with an AUC (area under the curve) value of 99%. When we prioritized reducing false negatives we found it resulted in more false positives. We found that false negatives occurred when participants made destabilizing joystick deflections that rapidly moved the MARS away from the balance point. These unpredictable destabilizing joystick deflections, which occurred in the duration of time after the input data, are likely a result of spatial disorientation. If our model could work in real time, we calculated that immediate human action would result in the prevention of 80.7% of crashes, however, if we accounted for human reaction times (∼400 ms), only 30.3% of crashes could be prevented, suggesting that one solution could be an AI taking temporary control of the spacecraft during these moments.

Funder

National Aeronautics and Space Administration

Air Force Office of Scientific Research

National Science Foundation

Publisher

Frontiers Media SA

Subject

Physiology (medical),Physiology

Reference47 articles.

1. The effect of hypergravity on upright balance and voluntary sway.;Bakshi;J. Neurophysiol.,2020

2. Perceived timing of vestibular stimulation relative to touch, light and sound.;Barnett-Cowan;Exp. Brain Res.,2009

3. Effects of directional uncertainty on visually-guided joystick pointing.;Berryhill;Percept. Mot. Skills,2005

4. Spatial disorientation in US Army rotary-wing operations.;Braithwaite;Aviat. Space Environ. Med.,1998

5. Learning phrase representations using RNN encoder-decoder for statistical machine translation.;Cho;arXiv,2014

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