Social robot navigation in environments with different population density
DOI:
https://doi.org/10.54097/hset.v41i.6791Keywords:
Modern robot. Reinforcement Learning, SimulationAbstract
In the field of modern robotics, robots need not only to avoid obstacles, but also to meet the comfort of pedestrians. In this paper, two methods of robot navigation: CP-SFM and reinforcement learning are introduced. CP-SFM model can analyse the repulsive force between the pedestrians and robot and generate a pedestrian-friendly path to the destination. Reinforcement learning method create a crowd-human interaction and use deep learning framework to train the robot learning human-robot and human-human interaction. These methods are also applied to the simulation environment and the results show the success of them.
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