  Ubiquitous robot control and human-robot collaboration using smart devices
poses a challenging problem primarily due to strict accuracy requirements and
sparse information. This paper presents a novel approach that incorporates a
probabilistic differentiable filter, specifically the Differentiable Ensemble
Kalman Filter (DEnKF), to facilitate robot control solely using Inertial
Measurement Units (IMUs) from a smartwatch and a smartphone. The implemented
system is cost-effective and achieves accurate estimation of the human pose
state. Experiment results from human-robot handover tasks underscore that smart
devices allow versatile and ubiquitous robot control. The code for this paper
is available at https://github.com/ir-lab/DEnKF and
https://github.com/wearable-motion-capture.
