In this paper, a method for online parameter estimation and automatic control of a system of rigidly attached quadcopters is introduced. First, the method performs an estimation of the physical structure attaching the quadcopters by relying solely on information from the quadcopters' Inertial Measurement Units (IMU). This information is obtained via simple and short online experiments, allowing their plug and play assembly without any human intervention. Then, given the estimated physical attachment's parameters, a stable operation of the quadcopters is achieved via an adaptive controller architecture, where the controller parameters are obtained using Reinforcement Learning. Finally, experimental results validate the proposed method, showing that a correct estimation of the physical structure is obtained allowing the autonomous flight of a pair of attached quadcopters.

The tactile internet will enable a new range of capabilities to enable immersive remote operations and interactions with a physical world. Tactile internet use cases span over many fields, from remote operation of industrial applications in, e.g., hazardous environments, via remote-controlled driving in a fully automated intelligent transport system, to remote surgery where the unique expert skills can be delivered to different locations in the world. Fifth-generation (5G) communication will play a fundamental part in this tactile internet vision, as it will provide necessary capabilities for the demanding communication needs in terms of reliability and low latency, for operators or teleoperated systems that are connected wirelessly. This paper provides an overview of tactile internet services and haptic interactions and communication. The 5G functionality for ultrareliable and low-latency services is described in depth and it is shown how 5G new radio (NR) and the evolved long-term evolution (LTE) radio interface can achieve guaranteed low-latency wireless transmission. The costs for providing reliable and low-latency wireless transmission in terms of reduced spectral efficiency and coverage are discussed. The 5G system architecture with a software-based network design based on a distributed cloud platform is presented. It is shown how the 5G network is configured for tactile internet services via multidomain orchestration.

This paper presents collaborative smoothing and mapping (C-SAM) as a viable approach to the multi-robot map- alignment problem. This method enables a team of robots to build joint maps with or without initial knowledge of their relative poses. To accomplish the simultaneous localization and mapping this method uses square root information smoothing (SRIS). In contrast to traditional extended Kalman filter (EKF) methods the smoothing does not exclude any information and is therefore also better equipped to deal with non-linear process and measurement models. The method proposed does not require the collaborative robots to have initial correspondence. The key contribution of this work is an optimal smoothing algorithm for merging maps that are created by different robots independently or in groups. The method not only joins maps from different robots, it also recovers the complete robot trajectory for each robot involved in the map joining. It is also shown how data association between duplicate features is done and how this reduces uncertainty in the complete map. Two simulated scenarios are presented where the C-SAM algorithm is applied on two individually created maps. One basically joins two maps resulting in a large map while the other shows a scenario where sensor extension is carried out.