Behaviors Coordination and Learning on Autonomous Navigation of Physical Robot
Abstract: Behaviors
coordination is one of keypoints in behavior based robotics. Subsumption
architecture and motor schema are example of their methods. In order to study
their characteristics, experiments in physical robot are needed to be done. It
can be concluded from experiment result that the first method gives quick,
robust but non smooth response. Meanwhile the latter gives slower but smoother
response and it is tending to reach target faster. Learning behavior improve
robot’s performance in handling uncertainty. Q learning is popular
reinforcement learning method that has been used in robot learning because it
is simple, convergent and off policy. The learning rate of Q affects robot’s
performance in learning phase. Q learning algorithm is implemented in
subsumption architecture of physical robot. As the result, robot succeeds to do
autonomous navigation task although it has some limitations in relation with
sensor placement and characteristic.
Author: Handy Wicaksono,
Handry Khoswanto, Son Kuswadi
Journal Code: jptkomputergg110057
