Abstract
In life science laboratories, the demand for automation is increasingly high. Laboratory automation is more complex than factory automation due to the varied laboratory environments and the need to adapt to different experimental requirements. This dissertation explores the integration of mobile robot systems into complex, distributed life science laboratories to achieve total laboratory automation. The study focuses on enhancing navigation, scheduling, and integration capabilities within these environments. A significant portion of the study involves adapting mobile robot systems to meet the unique demands of life science laboratory settings, emphasizing the deployment of a versatile mobile robot, the MOLAR, designed to streamline operations across various laboratory processes.
At the robot system level, the dissertation introduces the navigation methods of mobile robots. A detailed 2D environmental map was developed using LiDAR, incorporating semantic information to aid in precise movement and interaction in a complex laboratory environment. It also includes the design of transportation tools and charging strategies, and experiments were conducted to test the practical effectiveness of the robot navigation.
At the infrastructure level, the research advanced the integration of mobile robots with the laboratory's existing WiFi network, enabling efficient communication with automated doors and elevators. This section addresses the challenges of using laboratory automatic doors and elevators by developing a dedicated GUI in C# for realtime monitoring and control of the interactions between mobile robots and the elevator system, using IoT technology for precise detection of elevator doors and floors.
At the workflow control level, the mobile robot's control system, AIC, is integrated into the laboratory's high-level Workflow Management system. The mobile robot acts as a bridge connecting distributed workstations within the laboratory, receiving transport commands from SAMI. This enables a fully automated, 24/7 operational laboratory.
This dissertation provides comprehensive insights into the methodologies used for integrating mobile robots into life science laboratories. It offers substantial contributions to the field of robotics and automation, demonstrating the potential of mobile robots to enhance laboratory accuracy, efficiency, and productivity.
