5G Remote Control in Failure Situations of Transport Robots in Challenging Hospital Environments

Autonomous Mobile Robots (AMRs) continue to facilitate the work of physicians and hospital nurses by releasing those professionals from time consuming transport tasks within hospitals. Nonetheless, AMRs still often face challenges when situations occur, which result in a failure of the navigation system. In this paper, we present an analysis and an implementation of a remote-control mechanism using 5G networks to enable an operator to control an AMR, in our example within a hospital, to support an AMR in situations, where an autonomous navigation faced challenges, that cannot be solved autonomously. In detail, four major challenges are faced when implementing a remote control for failure situations – the data connection itself, the sensor data acquisition and compression, the delivery of the current robot state for a user and the controllability of the robot. For autonomous driving, the AMR is equipped with a 128-layered 3D-Lidar sensor. An RGB-D camera facilitates video feedback for the operator to navigate the AMR manually. Additionally, the point cloud of the 3D-lidar provides a detailed in-depth view of the environment, which recognizes present persons or also allows the operator to drive backwards.  To establish a connection between an AMR and a remote operator, a stable and low latency data connection is required. Since the Wi-Fi requirements of hospitals usually do not fit the requirements of remote-controlled robots regarding data security, network coverage, connection latency and bandwidth, the usage of the Wi-Fi network of hospitals is not appropriate.  These challenges can be overcome using 5G cellular network to guarantee a low latency, high bandwidth connection which is independent from the regulations and limitations of the local Wi-Fi network. Nonetheless, by selecting the cellular 5G network as the remote operation network, further challenges arise – e.g. coverage of the 5G network or the stable and secure accessibility of the robot. Since hospital building structures are complex and usually are constructed using reinforced concrete, 5G radio waves are reflected or absorbed. In addition, the bandwidth is limited, since a public cellular connection is used. Due to these limitations, data compression is required for transmitting large chunks of sensor data, such as RGB camera streams or point clouds. The RGB video compression is implemented using the H.264 codec, which again can be accelerated using hardware. The point cloud is compressed through an octree implementation. As a result, the sensor data is transmitted with low latency and less lag. Despite using data compression algorithms, which are not lossless, the quality of the sensor data, received by the operator, is still sufficient for remote control operations. For a safe and controlled remote control of an AMR using the above explained technology stack, a data connection with less to no data transfer loss is required.