Motion capture (MoCap) through tracking retroreflectors obtains high
precision pose estimation, which is frequently used in robotics. Unlike MoCap,
fiducial marker-based tracking methods do not require a static camera setup to
perform relative localization. Popular pose-estimating systems based on
fiducial markers have lower localization accuracy than MoCap. As a solution, we
propose Mobile MoCap, a system that employs inexpensive near-infrared cameras
for precise relative localization in dynamic environments. We present a
retroreflector feature detector that performs 6-DoF (six degrees-of-freedom)
tracking and operates with minimal camera exposure times to reduce motion blur.
To evaluate different localization techniques in a mobile robot setup, we mount
our Mobile MoCap system, as well as a standard RGB camera, onto a
precision-controlled linear rail for the purposes of retroreflective and
fiducial marker tracking, respectively. We benchmark the two systems against
each other, varying distance, marker viewing angle, and relative velocities.
Our stereo-based Mobile MoCap approach obtains higher position and orientation
accuracy than the fiducial approach.
The code for Mobile MoCap is implemented in ROS 2 and made publicly available
at https://github.com/RIVeR-Lab/mobile_mocap