ROS-Based Autonomous Navigation Robot Platform with Stepping Motor

Indoor navigation robots, which have been developed using a robot operating system, typically use a direct current motor as a motion actuator. Their control algorithm is generally complex and requires the cooperation of sensors such as wheel encoders to correct errors. For this study, an autonomous navigation robot platform named Owlbot was designed, which is equipped with a stepping motor as a mobile actuator. In addition, a stepping motor control algorithm was developed using polynomial equations, which can effectively convert speed instructions to generate control signals for accurately operating the motor. Using 2D LiDAR and an inertial measurement unit as the primary sensors, simultaneous localization, mapping, and autonomous navigation are realised based on the particle filtering mapping algorithm. The experimental results show that Owlbot can effectively map the unknown environment and realise autonomous navigation through the proposed control algorithm, with a maximum movement error being smaller than 0.015 m.

Automated summary

In this study, a autonomous navigation robot platform named Owlbot was designed, equipped with a stepping motor as a mobile actuator. A stepping motor control algorithm was developed using polynomial equations to accurately operate the motor. The platform used 2D LiDAR and an inertial measurement unit as primary sensors, and realized simultaneous localization, mapping, and autonomous navigation based on the particle filtering mapping algorithm. Experimental results showed that Owlbot effectively mapped unknown environments and achieved autonomous navigation with a maximum movement error smaller than 0.015 m.