Open AccessInvestigation of Preliminary Motions from a Static State and Their Predictability
Author(s) -
Chaoshun Xu,
Masahiro Fujiwara,
Yasutoshi Makino,
Hiroyuki Shinoda
Publication year - 2021
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.2021.p0537
Subject(s) - predictability , motion (physics) , movement (music) , task (project management) , jumping , computer science , artificial neural network , artificial intelligence , dynamics (music) , state (computer science) , mathematics , engineering , algorithm , physics , acoustics , physiology , statistics , systems engineering , biology
Humans observe the actions of others and predict their movements slightly ahead of time in everyday life. Many studies have been conducted to automate such a prediction ability computationally using neural networks; however, they implicitly assumed that preliminary motions occurred before significant movements. In this study, we quantitatively investigate when and how long a preliminary motion appears in motions from static states and what kinds of motion can be predicted in principle. We consider this knowledge fundamental for movement prediction in interaction techniques. We examined preliminary motions of basic movements such as kicking and jumping, and confirmed the presence of preliminary motions by using them as inputs to a neural network. As a result, although we did not find preliminary motion for a hand-moving task, a left-right jumping task had the most preliminary motion, up to 0.4 s before the main movement.