  Quadruped platforms have become an active topic of research due to their high
mobility and traversability in rough terrain. However, it is highly challenging
to determine whether the clattered environment could be passed by the robot and
how exactly its path should be calculated. Moreover, the calculated path may
pass through areas with dynamic objects or environments that are dangerous for
the robot or people around. Therefore, we propose a novel conceptual approach
of teaching quadruped robots navigation through user-guided path planning in
virtual reality (VR). Our system contains both global and local path planners,
allowing robot to generate path through iterations of learning. The VR
interface allows user to interact with environment and to assist quadruped
robot in challenging scenarios. The results of comparison experiments show that
cooperation between human and path planning algorithms can increase the
computational speed of the algorithm by 35.58% in average, and non-critically
increasing of the path length (average of 6.66%) in test scenario.
Additionally, users described VR interface as not requiring physical demand
(2.3 out of 10) and highly evaluated their performance (7.1 out of 10). The
ability to find a less optimal but safer path remains in demand for the task of
navigating in a cluttered and unstructured environment.
