Abstract:
Navigation among movable obstacles (NAMO) has been a research problem
for many robotics researchers. The work presented so far includes moving
obstacles out of the way and to plan shorter paths. However this interaction
with obstacles is based on either hit and try where a robot tries to move
obstacles one by one, or obstacles are labeled as movable and immovable.
Our work is based on learning if an obstacle is movable or immov able, and also finding out what is the best possible angle to push an obstacle
to move it. This has been done autonomously without human supervision,
where robot will keep interacting with various obstacles and will eventually
learn how to move obstacles out of the way. The developed algorithm is more
efficient, time and energy saving than the previously presented approaches.
