Safe Tightly-Constrained UAV Swarming in GNSS-denied Environments

Dmytruk, Andriy; Nascimento, Tiago P.; Ahmad, Afzal; Báča, Tomáš; Saska, Martin

doi:10.1109/icuas51884.2021.9476794

Cited by 10 publications

(10 citation statements)

References 14 publications

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“…This is done by using ultraviolet LEDs that emit particular optical identification signals, which are detected and decoded using cameras equipped with an optical filter that significantly attenuates most of the image background [98,101], and thus simplifies the detection of the optical signals on the camera frame. This method has been tested with great success in multiple real-world deployments of swarms and formations of UAVs [2,27,39,58,66,102,103].…”

Section: Sensory Equipmentmentioning

confidence: 99%

“…Nevertheless, bringing these swarm systems into the real world is a long-standing problem, due to the significant operative differences between laboratory environments and diverse, real-world environments. To deal with the demands of various real-world environments, the MRS platforms can be modified to handle the operating conditions required in plain fields, forests, dunes and deserts, hills, and much more [2,4,23,27,37,58,66,71]. One essential element of biologically-inspired swarming architectures is the perception-aware system, which allows for maintaining group cohesion and avoiding collisions between teammates.…”

Section: Swarming In Deserts Hills and Forestsmentioning

confidence: 99%

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MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems

Heřt

Báča

Petráček

et al. 2023

J Intell Robot Syst

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This paper presents a modular autonomous Unmanned Aerial Vehicle (UAV) platform called the Multi-robot Systems (MRS) Drone that can be used in a large range of indoor and outdoor applications. The MRS Drone features unique modularity with respect to changes in actuators, frames, and sensory configuration. As the name suggests, the platform is specially tailored for deployment within a MRS group. The MRS Drone contributes to the state-of-the-art of UAV platforms by allowing smooth real-world deployment of multiple aerial robots, as well as by outperforming other platforms with its modularity. For real-world multi-robot deployment in various applications, the platform is easy to both assemble and modify. Moreover, it is accompanied by a realistic simulator to enable safe pre-flight testing and a smooth transition to complex real-world experiments. In this manuscript, we present mechanical and electrical designs, software architecture, and technical specifications to build a fully autonomous multi UAV system. Finally, we demonstrate the full capabilities and the unique modularity of the MRS Drone in various real-world applications that required a diverse range of platform configurations.

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Section: Sensory Equipmentmentioning

confidence: 99%

Section: Swarming In Deserts Hills and Forestsmentioning

confidence: 99%

MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems

Heřt

Báča

Petráček

et al. 2023

J Intell Robot Syst

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“…12, where the swarm system showed the ability to follow uneven terrain. In works [26], [28], [46], a UAV swarm was deployed in a demanding forest environment. The compact group of robots was able to safely navigate through dense obstacle area using 2D LiDAR.…”

Section: Outdoor Real Robot Experimentsmentioning

confidence: 99%

MRS Modular UAV Hardware Platforms for Supporting Research in Real-World Outdoor and Indoor Environments

Hert,

Baca,

Petracek

et al. 2023

Preprint

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“…The cluster flocking category, on the other hand, encompasses those works where the designer chases the optimization of a system-level cost function tailored to control the policy of each agent in the swarm. Other works rely on schemes similar to the aforementioned one, for instance, Ali et al (2008), Kownacki andDaniel (2016), andDmytruk et al (2021). In 2018, Ali et al (2008) presented a new robotic platform called Kobot, equipped with an infrared sensor for measuring the distance between robots and obstacles, and a sensor for perceiving the relative headings of neighboring robots.…”

Section: State-of-the-artmentioning

confidence: 99%

“…A behavior based on proximal control and heading alignment is then put in place on such a platform and shown to be capable of generating self-organized flocking in a swarm. The most recent of the aforementioned works is that of Dmytruk et al (2021) . The work presents a bio-inspired decentralized flocking algorithm working in environments with high obstacle density that only relies on local perceptions.…”

Section: State-of-the-artmentioning

confidence: 99%

Adaptive arbitration of aerial swarm interactions through a Gaussian kernel for coherent group motion

et al. 2022

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Swarm behaviors offer scalability and robustness to failure through a decentralized and distributed design. When designing coherent group motion as in swarm flocking, virtual potential functions are a widely used mechanism to ensure the aforementioned properties. However, arbitrating through different virtual potential sources in real-time has proven to be difficult. Such arbitration is often affected by fine tuning of the control parameters used to select among the different sources and by manually set cut-offs used to achieve a balance between stability and velocity. A reliance on parameter tuning makes these methods not ideal for field operations of aerial drones which are characterized by fast non-linear dynamics hindering the stability of potential functions designed for slower dynamics. A situation that is further exacerbated by parameters that are fine-tuned in the lab is often not appropriate to achieve satisfying performances on the field. In this work, we investigate the problem of dynamic tuning of local interactions in a swarm of aerial vehicles with the objective of tackling the stability–velocity trade-off. We let the focal agent autonomously and adaptively decide which source of local information to prioritize and at which degree—for example, which neighbor interaction or goal direction. The main novelty of the proposed method lies in a Gaussian kernel used to regulate the importance of each element in the swarm scheme. Each agent in the swarm relies on such a mechanism at every algorithmic iteration and uses it to tune the final output velocities. We show that the presented approach can achieve cohesive flocking while at the same time navigating through a set of way-points at speed. In addition, the proposed method allows to achieve other desired field properties such as automatic group splitting and joining over long distances. The aforementioned properties have been empirically proven by an extensive set of simulated and field experiments, in communication-full and communication-less scenarios. Moreover, the presented approach has been proven to be robust to failures, intermittent communication, and noisy perceptions.

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Safe Tightly-Constrained UAV Swarming in GNSS-denied Environments

Cited by 10 publications

References 14 publications

MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems

MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems

MRS Modular UAV Hardware Platforms for Supporting Research in Real-World Outdoor and Indoor Environments

Adaptive arbitration of aerial swarm interactions through a Gaussian kernel for coherent group motion

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