10 research outputs found
Adaptive Cyber-Defense for Unmanned Aerial Vehicles: A Modular Simulation Model with Dynamic Performance Management
In light of escalating cyber threats, this study tackles the cybersecurity challenges in UAV systems, underscoring the limitations of static defense mechanisms. Traditional security approaches fall short against the sophisticated and evolving nature of cyber-attacks, particularly for UAVs that depend on real-time autonomy. Addressing this deficiency, we introduce an adaptive modular security system tailored for UAVs, enhancing resilience through real-time defensive adaptability. This system integrates scalable, modular components and employs machine learning techniques—specifically, neural networks and anomaly detection algorithm to improve threat prediction and response. Our approach marks a significant leap in UAV cybersecurity, departing from static defenses to a dynamic, context-aware strategy. By employing this system, UAV stakeholders gain the flexibility needed to counteract multifaceted cyber risks in diverse operational scenarios. The paper delves into the system's design and operational efficacy, juxtaposing it with conventional strategies. Experimental evaluations, using varied UAV scenarios, measure defense success rates, computational efficiency, and resource utilization. Findings reveal that our system surpasses traditional models in defense success and computational speed, albeit with a slight increase in resource usage a consideration for deployment in resource-constrained contexts. In closing, this research underscores the imperative for dynamic, adaptable cybersecurity solutions in UAV operations, presenting an innovative and proactive defense framework. It not only illustrates the immediate benefits of such adaptive systems but also paves the way for ongoing enhancements in UAV cyber defense mechanisms
Optimal Trajectory Planning for Cinematography with Multiple Unmanned Aerial Vehicles
This paper presents a method for planning optimal trajectories with a team of
Unmanned Aerial Vehicles (UAVs) performing autonomous cinematography. The
method is able to plan trajectories online and in a distributed manner,
providing coordination between the UAVs. We propose a novel non-linear
formulation for this challenging problem of computing multi-UAV optimal
trajectories for cinematography; integrating UAVs dynamics and collision
avoidance constraints, together with cinematographic aspects like smoothness,
gimbal mechanical limits and mutual camera visibility. We integrate our method
within a hardware and software architecture for UAV cinematography that was
previously developed within the framework of the MultiDrone project; and
demonstrate its use with different types of shots filming a moving target
outdoors. We provide extensive experimental results both in simulation and
field experiments. We analyze the performance of the method and prove that it
is able to compute online smooth trajectories, reducing jerky movements and
complying with cinematography constraints.Comment: This paper has been published as: Optimal trajectory planning for
cinematography with multiple Unmanned Aerial Vehicles. Alfonso Alcantara and
Jesus Capitan and Rita Cunha and Anibal Ollero. Robotics and Autonomous
Systems. 103778 (2021) 10.1016/j.robot.2021.10377
Autonomous Execution of Cinematographic Shots with Multiple Drones
This paper presents a system for the execution of autonomous cinematography
missions with a team of drones. The system allows media directors to design
missions involving different types of shots with one or multiple cameras,
running sequentially or concurrently. We introduce the complete architecture,
which includes components for mission design, planning and execution. Then, we
focus on the components related to autonomous mission execution. First, we
propose a novel parametric description for shots, considering different types
of camera motion and tracked targets; and we use it to implement a set of
canonical shots. Second, for multi-drone shot execution, we propose distributed
schedulers that activate different shot controllers on board the drones.
Moreover, an event-based mechanism is used to synchronize shot execution among
the drones and to account for inaccuracies during shot planning. Finally, we
showcase the system with field experiments filming sport activities, including
a real regatta event. We report on system integration and lessons learnt during
our experimental campaigns
Versatile Multilinked Aerial Robot with Tilting Propellers: Design, Modeling, Control and State Estimation for Autonomous Flight and Manipulation
Multilinked aerial robot is one of the state-of-the-art works in aerial
robotics, which demonstrates the deformability benefiting both maneuvering and
manipulation. However, the performance in outdoor physical world has not yet
been evaluated because of the weakness in the controllability and the lack of
the state estimation for autonomous flight. Thus we adopt tilting propellers to
enhance the controllability. The related design, modeling and control method
are developed in this work to enable the stable hovering and deformation.
Furthermore, the state estimation which involves the time synchronization
between sensors and the multilinked kinematics is also presented in this work
to enable the fully autonomous flight in the outdoor environment. Various
autonomous outdoor experiments, including the fast maneuvering for interception
with target, object grasping for delivery, and blanket manipulation for
firefighting are performed to evaluate the feasibility and versatility of the
proposed robot platform. To the best of our knowledge, this is the first study
for the multilinked aerial robot to achieve the fully autonomous flight and the
manipulation task in outdoor environment. We also applied our platform in all
challenges of the 2020 Mohammed Bin Zayed International Robotics Competition,
and ranked third place in Challenge 1 and sixth place in Challenge 3
internationally, demonstrating the reliable flight performance in the fields