Robotic Patrolling Systems based on Hidden Markov Model for Moving Visitors
Satoshi Hoshino, Junichiro Chiba · 2018
This paper presents a robotic patrolling system for moving visitors. A mobile robot equipped with a sensor for human detection is used in this system. The patrol mission for the robot is to detect as many visitors as possible. The visitors move toward their destinations. Thus the robot is required to monitor what they are doing at their destinations rather than the moving paths. For this challenge, we propose an optimal patrolling strategy considering the destinations. However, since the detectable range of the sensor is limited, the robot can only observe the environment locally. In order to correctly estimate the moving destinations of visitors from the local information, we use a Hidden Markov Model, HMM. The estimated destinations are used as a reward function in the value iteration method. Finally, the patrolling simulations show that the robot is enabled to detect more visitors by monitoring their destinations. Through the results, we discuss the effectiveness of the robotic system for moving visitors.