Yusuke Tsunoda, Shoken Otsuka, Kazuki Ito, Runze Xiao, Keisuke Naniwa, Yuichiro Sueoka, Koichi Osuka
2024年10月17日
Recently, the navigation of mobile robots in unknown environments has become
a particularly significant research topic. Previous studies have primarily
employed real-time environmental mapping using cameras and LiDAR, along with
self-localization and path generation based on those maps. Additionally, there
is research on Sim-to-Real transfer, where robots acquire behaviors through
pre-trained reinforcement learning and apply these learned actions in
real-world navigation. However, strictly the observe action and modelling of
unknown environments that change unpredictably over time with accuracy and
precision is an extremely complex endeavor. This study proposes a simple
navigation algorithm for traversing unknown environments by utilizes the number
of swarm robots. The proposed algorithm assumes that the robot has only the
simple function of sensing the direction of the goal and the relative positions
of the surrounding robots. The robots can navigate an unknown environment by
simply continuing towards the goal while bypassing surrounding robots. The
method does not need to sense the environment, determine whether they or other
robots are stuck, or do the complicated inter-robot communication. We
mathematically validate the proposed navigation algorithm, present numerical
simulations based on the potential field method, and conduct experimental
demonstrations using developed robots based on the sound fields for navigation.