Related papers: Connectivity Preserving Decentralized UAV Swarm Na…
This paper presents a scalable online algorithm to generate safe and kinematically feasible trajectories for quadrotor swarms. Existing approaches rely on linearizing Euclidean distance-based collision constraints and on axis-wise…
The paper considers the problem of controlling Connected and Automated Vehicles (CAVs) traveling through a three-entry roundabout so as to jointly minimize both the travel time and the energy consumption while providing speed-dependent…
We address the problem of controlling Connected and Automated Vehicles (CAVs) in conflict areas of a traffic network subject to hard safety constraints. It has been shown that such problems can be solved through a combination of tractable…
Control barrier functions (CBFs) enable guaranteed safe multi-agent navigation in the continuous domain. The resulting navigation performance, however, is highly sensitive to the underlying hyperparameters. Traditional approaches consider…
This paper considers how to ensure that a system of fixed wing Unmanned Aerial Vehicles (UAVs) can avoid collisions. To do so we develop a novel method for creating a barrier function, which is similar to a Lyapunov function and can be used…
This paper presents a deep reinforcement learning (DRL) based controller for collective navigation of unmanned aerial vehicle (UAV) swarms in communication-denied environments, enabling robust operation in complex, obstacle-rich…
Safe real-time control of robotic manipulators in unstructured environments requires handling numerous safety constraints without compromising task performance. Traditional approaches, such as artificial potential fields (APFs), suffer from…
This article presents a unique framework for deploying decentralized and infrastructure-independent swarms of homogeneous aerial vehicles in the real world without explicit communication. This is a requirement in swarm research, which…
This paper investigates the control of a massive population of UAVs such as drones. The straightforward method of control of UAVs by considering the interactions among them to make a flock requires a huge inter-UAV communication which is…
Unmanned aerial vehicle (UAV) swarms must exploit machine learning (ML) in order to execute various tasks ranging from coordinated trajectory planning to cooperative target recognition. However, due to the lack of continuous connections…
Cellular-connected unmanned aerial vehicle (UAV) swarm is a promising solution for diverse applications, including cargo delivery and traffic control. However, it is still challenging to communicate with and control the UAV swarm with high…
We address the problem of controlling Connected and Automated Vehicles (CAVs) in conflict areas of a traffic network subject to hard safety constraints. It has been shown that such problems can be solved through a combination of tractable…
The cooperative control of the connected and automated vehicle (CAV) is recognized as an effective approach to alleviate traffic congestion and improve traffic safety, especially for on-ramp bottlenecks. However, in the mixed traffic, the…
The paper focuses on the design of a control strategy for safety-critical remote teleoperation. The main goal is to make the controlled system track the desired velocity specified by an operator while avoiding obstacles despite…
In recent years, Unmanned Aerial Vehicles (UAVs) have been utilized as effective platforms for carrying Wi-Fi Access Points (APs) and cellular Base Stations (BSs), enabling low-cost, agile, and flexible wireless networks with high Quality…
The capability to navigate safely in an unstructured environment is crucial when deploying robotic systems in real-world scenarios. Recently, control barrier function (CBF) based approaches have been highly effective in synthesizing…
Safe and agile trajectory planning is essential for autonomous systems, especially during complex aerobatic maneuvers. Motivated by the recent success of diffusion models in generative tasks, this paper introduces AeroTrajGen, a novel…
UAV swarms can form virtual antenna arrays to exploit additional spatial degrees of freedom and enhance integrated sensing and communication (ISAC). The optimization of UAV positions is challenging due to the distributed nature of swarms…
We introduce AttentionSwarm, a novel benchmark designed to evaluate safe and efficient swarm control in a dynamic drone racing scenario. Central to our approach is the Attention Model-Based Control Barrier Function (CBF) framework, which…
This paper studies a new latency optimization problem in unmanned aerial vehicles (UAVs)-enabled federated learning (FL) with integrated sensing and communication. In this setup, distributed UAVs participate in model training using sensed…