3 accepted papers
Data-driven methods based on neural networks are becoming more widespread for predicting human lower-limb motion. Until now, however, actual examples have focused on only a handful, steady locomotion behaviors. Here we explore if neural network predictors can simultaneously cover many more behaviors…
Motion planning for mobile robots with many degrees-of-freedom (DoF) is challenging due to their high-dimensional configuration spaces. To manage this curse of dimensionality, this paper proposes a new hierarchical framework that decomposes the system into sub-systems (based on shared capabilities o…
Many quadrupedal animals have lateral degrees of freedom in their backs that assist locomotion. This paper seeks to use a robotic model to demonstrate that back bending assists not only forward motion, but also lateral and turning motions. This paper uses geometric mechanics to prescribe gaits that…