Automating processes with the increased use of robots is one of the key vertical applications enabled by 6G. Sensing the surrounding environment, localization and communication become crucial factors for these robots to operate. Light detection and ranging (LiDAR) has emerged as an appropriate method for sensing due to its capability generating detail-rich positional information with high accuracy. However, LiDARs are power-hungry devices that generate bulk amounts of data, limiting their use as on-board sensors in robots. In this paper, we present a novel approach to the methodology of generating an enhanced 3D map with improved field-of-view using multiple LiDAR sensors. This offloads the sensing burden from robots to the infrastructure where a centralized communication network will establish localization. We utilize an inherent property of LiDAR point clouds; point rings with Inertial Measurement Unit (IMU) data embedded in the sensor for point cloud registration. The generated 3D point cloud map has an accuracy of 10 cm compared to the real-world measurements. We also carry out a proof of concept design of the proposed method using two LiDAR sensors fixed in the infrastructure at elevated positions. This extends to an application where a robot is navigated through the mapped environment using a wireless link with minimal support from the on-board sensors. Our results further validate the idea of using multiple elevated LiDARs as a part of the infrastructure for various localization applications.