Cloud-Based Autonomous Indoor Navigation: A Case Study
This is an incremental case study for robotics and cloud computing applications in indoor navigation.
The authors tackled autonomous indoor navigation by designing a cloud-enabled robotic system that offloads heavy computation to the cloud, resulting in significantly shorter map-building times and more accurate maps in autonomous mode compared to manual mode.
In this case study, we design, integrate and implement a cloud-enabled autonomous robotic navigation system. The system has the following features: map generation and robot coordination via cloud service and video streaming to allow online monitoring and control in case of emergency. The system has been tested to generate a map for a long corridor using two modes: manual and autonomous. The autonomous mode has shown more accurate map. In addition, the field experiments confirm the benefit of offloading the heavy computation to the cloud by significantly shortening the time required to build the map.