The need for automated material handling inside the factory has been steadily increasing, especially due to implementation of intelligent manufacturing for better productivity and product quality. Automated material handling devices include logistics robots, automated guided vehicles, industrial robots, collaborative robots, and pick-and-place devices. This study focuses on the development of a low-cost logistics robot that works effectively within a simulated smart factory environment. A nominal PID controller is implemented to guide the robot to follow the line painted on the factory floor. The tracking error information is generated by four down-facing infrared sensors and is fed into the controller. The line-following performance is significantly improved with augmentation of a model-based friction compensator. Optimization of battery power depending on the remaining charge status enhances the reliability. All hardware/software development is supported by the Arduino platform. The step-by-step movement and performance of the logistics robot is verified inside the simulated smart factory environment that includes a robot arm, three conveyors, and two processing stations.

Actuators for exoskeleton robots comprise various types such as electric, hydraulic, and pneumatic and it is necessary to apply the correct actuator according to the purpose. Most exoskeleton robots mainly use electric actuators, and some special-purpose robots, such as for heavy-load transport requiring large force, use hydraulic actuators. In this paper, friction of the actuation module consisting of a harmonic drive and a brushless DC motor is measured through experiments. And the friction characteristics of the actuation module are analyzed. The harmonic drive transmission system has various advantages, but it also has hysteresis and nonlinear friction characteristics. The friction compensation control of the actuation module enables precise control of the exoskeleton robot, and improves the robot’s performance. Appropriate friction model selection and design affects friction compensation performance. In this study, static and dynamic friction models are designed and analyzed based on the friction data of the actuation module.