A new class of Multi-Rotor Aerial Vehicles (MRAVs), known as omnidirectional MRAVs (o-MRAVs), has attracted significant interest in the robotics community. These MRAVs have the unique capability of independently controlling their 3D position and 3D orientation. In the context of aerial communication networks, this translates into the ability to control the position and orientation of the antenna mounted on the MRAV without any additional devices tasked for antenna orientation. This additional Degrees of Freedom (DoF) adds a new dimension to aerial communication systems, creating various research opportunities in communications-aware trajectory planning and positioning. This paper presents this new class of MRAVs and discusses use cases in areas such as physical layer security and optical communications. Furthermore, the benefits of these MRAVs are illustrated with realistic simulation scenarios. Finally, new research problems and opportunities introduced by this advanced robotics technology are discussed.

The integration of Multi-Rotor Aerial Vehicles (MRAVs) into 5G and 6G networks enhances coverage, connectivity, and congestion management. This fosters communication-aware robotics, exploring the interplay between robotics and communications, but also makes the MRAVs susceptible to malicious attacks, such as jamming. One traditional approach to counter these attacks is the use of beamforming on the MRAVs to apply physical layer security techniques. In this paper, we explore pose optimization as an alternative approach to countering jamming attacks on MRAVs. This technique is intended for omnidirectional MRAVs, which are drones capable of independently controlling both their position and orientation, as opposed to the more common underactuated MRAVs whose orientation cannot be controlled independently of their position. In this paper, we consider an omnidirectional MRAV serving as a Base Station (BS) for legitimate ground nodes, under attack by a malicious jammer. We optimize the MRAV pose (i.e., position and orientation) to maximize the minimum Signal-to-Interference-plus-Noise Ratio (SINR) over all legitimate nodes.

This paper proposes a method for designing human-robot collaboration tasks and generating corresponding trajectories. The method uses high-level specifications, expressed as a Signal Temporal Logic (STL) formula, to automatically synthesize task assignments and trajectories. To illustrate the approach, we focus on a specific task: a multi-rotor aerial vehicle performing object handovers in a power line setting. The motion planner considers limitations, such as payload capacity and recharging constraints, while ensuring that the trajectories are feasible. Additionally, the method enables users to specify robot behaviors that take into account human comfort (e.g., ergonomics, preferences) while using high-level goals and constraints. The approach is validated through numerical analyzes in MATLAB and realistic Gazebo simulations using a mock-up scenario.

This paper presents a method for designing energy-aware collaboration tasks between humans and robots, and generating corresponding trajectories to carry out those tasks. The method involves using high-level specifications expressed as Signal Temporal Logic (STL) specifications to automatically synthesize task assignments and trajectories. The focus is on a specific task where a Multi-Rotor Aerial Vehicle (MRAV) performs object handovers in a power line setting. The motion planner takes into account constraints such as payload capacity and refilling, while ensuring that the generated trajectories are feasible. The approach also allows users to specify robot behaviors that prioritize human comfort, including ergonomics and user preferences. The method is validated through numerical analyses in MATLAB and realistic Gazebo simulations in a mock-up scenario.

This paper presents a theoretical study on the ability of multi-rotor aerial vehicles (MRAVs) with tiltable propellers to achieve and sustain static hovering at different orientations. To analyze the ability of MRAVs with tiltable propellers to achieve static hovering, a novel linear map between the platform's control inputs and applied forces and moments is introduced. The relation between the introduced map and the platform's ability to hover at different orientations is developed. Correspondingly, the conditions for MRAVs with tiltable propellers to realize and sustain static hovering are detailed. A numerical metric is then introduced, which reflects the ability of MRAVs to sustain static hovering at different orientations. A subclass of MRAVs with tiltable propellers is defined as the Critically Statically Hoverable platforms (CSH), where CSH platforms are MRAVs that cannot sustain static hovering with fixed propellers, but can achieve static hovering with tilting propellers. Finally, extensive simulations are conducted to test and validate the above findings, and to demonstrate the effect of the proposed numerical metric on the platform's dynamics.