Research and advancements in hybrid airships—A review

Manikandan, M.; Pant, Rajkumar S.

doi:10.1016/j.paerosci.2021.100741

Cited by 28 publications

(3 citation statements)

References 109 publications

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“…They are also safer than other platforms if failure or degradation occurs, as they descend slowly to the ground in such cases. The combination of these features with the notable evolution in aerial robotics in the last 20 years has led to a resurgence in interest in the development of airship applications like cargo transportation [2], telecommunications [3] and environmental monitoring [4].…”

Section: Introductionmentioning

confidence: 99%

Hexa-Propeller Airship for Environmental Surveillance and Monitoring in Amazon Rainforest

Azinheira,

Carvalho,

Paiva

et al. 2024

Aerospace

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This paper proposes a new kind of airship actuator configuration for surveillance and environmental monitoring missions. We present the design and application of a six-propeller electrical airship (Noamini) with independent tilting propellers, allowing improved and flexible maneuverability. The vehicle has different combinations of differential propulsion and can be used in a two-, four- or six-motor configuration. We developed a high-fidelity airship simulator for the Noamini airship, which was used to test and validate a control/guidance approach. Incremental Nonlinear Dynamic Inversion (INDI) is used for the velocity/attitude control to follow a high-level L1 guidance reference in a simulated waypoint-tracking mission with wind and turbulence. The proposed framework will be soon implemented in the onboard control system of the Noamini, an autonomous airship for environmental monitoring and surveillance applications.

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Section: Introductionmentioning

confidence: 99%

Hexa-Propeller Airship for Environmental Surveillance and Monitoring in Amazon Rainforest

Azinheira,

Carvalho,

Paiva

et al. 2024

Aerospace

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“…We increasingly deploy autonomous systems in the air and oceans. Beyond airplanes and ships, there are emerging applications such as balloons in the stratosphere for delivering internet access [1], airships, ocean gliders and active drifters for collecting ocean data [2]- [5], floating solar farms storing energy in fuels [6], and floating seaweed farms for biomass and carbon sequestration [7], [8].…”

Section: Introductionmentioning

confidence: 99%

“…For that we build on the recent Multi-Time HJ Reachability formulation [42] for computing a time-optimal value function (Time-to-reach) on the latest forecast and use it for closed-loop control. This can be thought of as full-time horizon MPC at every step; (2) We are the first to evaluate and compare the reliability of closed-loop control schemes for underactuated agents in ocean flows in the setting of daily forecasts with realistic forecast error. We evaluate performance across a large set of multi-day start-to-target missions distributed spatially across the Gulf of Mexico and temporally across four months using HYCOM and Copernicus Ocean Forecasts [10], [11] We compare several methods on this dataset across multiple metrics and find that our control architecture significantly outperforms other methods in terms of reliability; (3) We quantify how the reliability of various control methods is affected by the forecast error.…”

Section: Introductionmentioning

confidence: 99%

Navigating Underactuated Agents by Hitchhiking Forecast Flows

Wiggert

Doshi

Lermusiaux

et al. 2022

2022 IEEE 61st Conference on Decision and Control (CDC)

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In dynamic flow fields such as winds and ocean currents an agent can navigate by going with the flow, only using minimal propulsion to nudge itself into beneficial flows. This navigation paradigm of hitchhiking flows is highly energyefficient. However, reliable navigation in this setting remains challenging as typically only forecasts are available which differ significantly from the true currents and the forecast error can be larger than can be handled by the actuation of the agent. In this paper, we propose a novel control method for reliable navigation of underactuated agents hitchhiking flows based on imperfect forecasts. In the spirit of Model Predictive Control our method allows for time-optimal replanning at every time step with only one computation per forecast. Using the recent Multi-Time Hamilton-Jacobi Reachability formulation we obtain a value function which is then used for closed-loop control. We evaluate the reliability of our method empirically over a large set of multi-day start-target missions in the ocean currents of the Gulf of Mexico with realistic forecast errors. Our method outperforms the baselines significantly, achieving high reliability, measured as the success rate of navigating from start to target, at low computational cost.

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