Integration of Fully-Actuated Multirotors into Real-World Applications

Keipour, Azarakhsh; Mousaei, Mohammadreza; Ashley, Andrew T; Scherer, Sebastian

doi:10.48550/arxiv.2011.06666

Cited by 5 publications

(6 citation statements)

References 5 publications

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“…Currently, there are various controllers implemented in the simulator that can be customized, ranging from simple nested PID loops for position and attitude controllers to Hybrid Position-Force controller (HPFC) [10], [17] and customized controllers for fixed-wing and hybrid VTOLs [5], [19]. Figure 3 illustrates an example of automatic analysis provided during the controller design.…”

Section: Controller Designmentioning

confidence: 99%

“…The rapid growth of Unmanned Aerial Vehicle (UAV) systems has resulted in reduced costs and increased researchers' attention to UAV development. New applications are introduced every day for free flight [1], [2], [3], [4], and new designs are introduced (e.g., fully-actuated multirotors and hybrid VTOLs [5]) to allow even more applications that extend to aerial manipulation and physical interaction of these robots with their environment [6], [7], [8], [9], [10].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

UAS Simulator for Modeling, Analysis and Control in Free Flight and Physical Interaction

Keipour

Mousaei

Geng

et al. 2023

AIAA SCITECH 2023 Forum

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This workshop paper presents the challenges we encountered when simulating fully-actuated Unmanned Aerial Vehicles (UAVs) for our research and the solutions we developed to overcome the challenges. We describe the ARCAD simulator that has helped us rapidly implement and test different controllers ranging from Hybrid Force-Position Controllers to advanced Model Predictive Path Integrals and has allowed us to analyze the design and behavior of different fullyactuated UAVs. We used the simulator to enable real-world deployments of our fully-actuated UAV fleet for different applications. The simulator is further extended to support the physical interaction of UAVs with their environment and allow more UAV designs, such as hybrid VTOLs. The code for the simulator can be accessed from https://github.com/ keipour/aircraft-simulator-matlab.

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Section: Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

UAS Simulator for Modeling, Analysis and Control in Free Flight and Physical Interaction

Keipour

Mousaei

Geng

et al. 2023

AIAA SCITECH 2023 Forum

View full text Add to dashboard Cite

show abstract

“…(Keipour et al, 2021a) also uses IBVS for landing on a moving platform in MBZIRC 2017. Stable aerial manipulation tasks might also be performed with fully-actuated UAVs (Rajappa et al, 2015;Keipour et al, 2020;Odelga et al, 2016).…”

Section: Related Workmentioning

confidence: 99%

Mission-level Robustness with Rapidly-deployed, Autonomous Aerial Vehicles by Carnegie Mellon Team Tartan at MBZIRC 2020

Bhattacharya¹,

Gandhi²,

Merkle³

et al. 2022

Self Cite

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For robotic systems to succeed in high risk, real-world situations, they have to be quickly deployable and robust to environmental changes, under-performing hardware, and mission subtask failures. These robots are often designed to consider a single sequence of mission events, with complex algorithms lowering individual subtask failure rates under some critical constraints. Our approach utilizes common techniques in vision and control, and encodes robustness into mission structure through outcome monitoring and recovery strategies. In addition, our system infrastructure enables rapid deployment and requires no central communication. This report also includes lessons in rapid field robotic development and testing. We developed and evaluated our systems through real-robot experiments at an outdoor test site in Pittsburgh, Pennsylvania, USA, as well as in the 2020 Mohamed Bin Zayed International Robotics Challenge. All competition trials were completed in fully autonomous mode without RTK-GPS. Our system placed fourth in Challenge 2 and seventh in the Grand Challenge, with notable achievements such as popping five balloons (Challenge 1), successfully picking and placing a block (Challenge 2), and dispensing the most water onto an outdoor, real fire with an autonomous UAV (Challenge 3).

show abstract

Section: Related Workmentioning

confidence: 99%

Carnegie Mellon Team Tartan: Mission-level Robustness with Rapidly Deployed Autonomous Aerial Vehicles in the MBZIRC 2020

Bhattacharya¹,

Gandhi²,

Merkle³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

For robotics systems to be used in high risk, real-world situations, they have to be quickly deployable and robust to environmental changes, under-performing hardware, and mission subtask failures. Robots are often designed to consider a single sequence of mission events, with complex algorithms lowering individual subtask failure rates under some critical constraints. Our approach is to leverage common techniques in vision and control and encode robustness into mission structure through outcome monitoring and recovery strategies, aided by a system infrastructure that allows for quick mission deployments under tight time constraints and no central communication. We also detail lessons in rapid field robotics development and testing. Systems were developed and evaluated through real-robot experiments at an outdoor test site in Pittsburgh, Pennsylvania, USA, as well as in the 2020 Mohamed Bin Zayed International Robotics Challenge. All competition trials were completed in fully autonomous mode without RTK-GPS. Our system led to 4th place in Challenge 2 and 7th place in the Grand Challenge, and achievements like popping five balloons (Challenge 1), successfully picking and placing a block (Challenge 2), and dispensing the most water autonomously with a UAV of all teams onto an outdoor, real fire (Challenge 3).

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Integration of Fully-Actuated Multirotors into Real-World Applications

Cited by 5 publications

References 5 publications

UAS Simulator for Modeling, Analysis and Control in Free Flight and Physical Interaction

UAS Simulator for Modeling, Analysis and Control in Free Flight and Physical Interaction

Mission-level Robustness with Rapidly-deployed, Autonomous Aerial Vehicles by Carnegie Mellon Team Tartan at MBZIRC 2020

Carnegie Mellon Team Tartan: Mission-level Robustness with Rapidly Deployed Autonomous Aerial Vehicles in the MBZIRC 2020

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