DARWIN: <u>D</u> igital Twin <u>A</u> ssisted <u>R</u> obot Navigation and <u>WI</u> reless <u>N</u> etwork Management

Automated warehouses involve robots that move across the floor, avoiding obstacles while remaining connected via an access point (AP) to a central controller that instructs the robots. The complex propagation environment and presence of metallic surfaces results in spotty coverage, which changes over time as the location of stored products and machinery changes. Thus, maintaining an assured connectivity to APs while performing navigation is a challenge, although it is needed to relay local sensor data from the robots to the controller and receive directions from the latter. <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm{DARWIN}$</tex-math></inline-formula>, involves creating a digital twin of the warehouse for training the robots by jointly optimizing the navigation and avoiding wireless dead-spots. <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm{DARWIN}$</tex-math></inline-formula> has three key capabilities: First, it captures the features of both physical and RF environments in the digital world. Second, it allows real-time updating of the digital twin if significant disparity is detected compared to the physical environment. Finally, it includes a reinforcement learning algorithm that jointly optimizes navigation and network resource management, while accounting for handover and outage. We validate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm{DARWIN}$</tex-math></inline-formula> on an emulation environment consisting of Robot Operating System and Gazebo platforms along with real-world RF measurements. Results reveal that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm{DARWIN}$</tex-math></inline-formula> reduces the number of steps by 43% compared to choosing the closest AP, while detecting environmental changes with maximum 96% accuracy to maintain a high-fidelity digital twin.