リーマン幾何学による人間の動作解析と動作転送
A Riemannian Take on Human Motion Analysis and Retargeting
人間の腕の動作をリーマン幾何学に基づく測地線シナジーの系列としてモデル化し、姿勢や手先軌道を予測するとともに、その解析をロボットへの動作転送に応用した研究。
著者: Holger Klein, Noémie Jaquier, Andre Meixner, Tamim Asfour
分類: cs.RO
原文アブストラクト
Dynamic motions of humans and robots are widely driven by posture-dependent nonlinear interactions between their degrees of freedom. However, these dynamical effects remain mostly overlooked when studying the mechanisms of human movement generation. Inspired by recent works, we hypothesize that human motions are planned as sequences of geodesic synergies, and thus correspond to coordinated joint movements achieved with piecewise minimum energy. The underlying computational model is built on Riemannian geometry to account for the inertial characteristics of the body. Through the analysis of various human arm motions, we find that our model segments motions into geodesic synergies, and successfully predicts observed arm postures, hand trajectories, as well as their respective velocity profiles. Moreover, we show that our analysis can further be exploited to transfer arm motions to robots by reproducing individual human synergies as geodesic paths in the robot configuration space.
