Swarm of Inexpensive Heterogeneous Micro Aerial Vehicles

Thakur, Dinesh; Tao, Yuezhan; Li, Rebecca; Zhou, Alex; Kushleyev, Alex; Kumar, Vijay

doi:10.1007/978-3-030-71151-1_37

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…Ge et al [15] used this setup in a MAV swarm system for decentralized vision-based detection and tracking strategies. On the same topic, Thakur et al [16] instead used the successor of the previously mentioned board. These works depict examples of lightweight vision-based platforms using smartphone processors with weights under 450 g. These platforms are lightweight enough to be both agile and resistant in case of collisions, and as such are a good prototype for testing new algorithms.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments

Mugnai

Losè

Herrera-Alarcon

et al. 2023

Drones

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Nowadays, multirotors are versatile systems that can be employed in several scenarios, where their increasing autonomy allows them to achieve complex missions without human intervention. This paper presents a framework for autonomous missions with low-cost Unmanned Aerial Vehicles (UAVs) in Global Navigation Satellite System-denied (GNSS-denied) environments. This paper presents hardware choices and software modules for localization, perception, global planning, local re-planning for obstacle avoidance, and a state machine to dictate the overall mission sequence. The entire software stack has been designed exploiting the Robot Operating System (ROS) middleware and has been extensively validated in both simulation and real environment tests. The proposed solution can run both in simulation and in real-world scenarios without modification thanks to a small sim-to-real gap with PX4 software-in-the-loop functionality. The overall system has competed successfully in the Leonardo Drone Contest, an annual competition between Italian Universities with a focus on low-level, resilient, and fully autonomous tasks for vision-based UAVs, proving the robustness of the entire system design.

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Section: Related Workmentioning

confidence: 99%

An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments

Mugnai

Losè

Herrera-Alarcon

et al. 2023

Drones

View full text Add to dashboard Cite

show abstract

“…Although the computations are performed onboard, GNSS information is collected and shared among vehicles to generate relative position information, which is not always reliable. Other works with real-world implementations include dynamic encirclement [9], outdoor predictive flocking [10], formation in motion [11], formation with communication constraints [12] and indoor forma-tion with visual-inertial odometry [14]. However, the works listed previously relies on global localization systems and/or offboard computation and/or shared coordinate frames and/or reliable communication network.…”

Section: Introductionmentioning

confidence: 99%

A Distributed Architecture for Onboard Tightly-Coupled Estimation and Predictive Control of Micro Aerial Vehicle Formations

Erunsal,

Ventura,

Martinoli

2024

Springer Proceedings in Advanced Robotics

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This paper presents a distributed estimation and control architecture for leader-follower formations of multi-rotor micro aerial vehicles. The architecture involves multi-rate extended Kalman filtering and nonlinear model predictive control in order to optimize the system performance while satisfying various physical constraints of the vehicles, such as actuation limits, safety thresholds and perceptual restrictions. The architecture leverages exclusively onboard sensing, computation, and communication resources and it has been designed for enhanced robustness to perturbations thanks to its tightly coupled components. The architecture has been initially tested and calibrated in a high-fidelity robotic simulator and then validated with a real two-vehicle system engaged in formation navigation and reconfiguration tasks. The results not only show the high formation performance of the architecture while satisfying numerous constraints but also indicate that it is possible to achieve full navigation and coordination autonomy in presence of severe resource constraints as those characterizing micro aerial vehicles.

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Vision-based Relative Detection and Tracking for Teams of Micro Aerial Vehicles

Lee

Radhakrishnan

et al. 2022

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Swarm of Inexpensive Heterogeneous Micro Aerial Vehicles

Cited by 4 publications

References 25 publications

An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments

An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments

A Distributed Architecture for Onboard Tightly-Coupled Estimation and Predictive Control of Micro Aerial Vehicle Formations

Vision-based Relative Detection and Tracking for Teams of Micro Aerial Vehicles

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