Design of multirotor aerial vehicles: A taxonomy based on input allocation

Hamandi, Mahmoud; Usai, Federico; Sablé, Quentin; Staub, Nicolas; Tognon, Marco; Franchi, Antonio

doi:10.1177/02783649211025998

Cited by 71 publications

(56 citation statements)

References 97 publications

(143 reference statements)

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“…and f c is computed as in (3). For the sake of deriving the control law and proving the asymptotic stability in nominal conditions, we consider zero human forces u H = 0 and modeling errors δ = 0.…”

Section: Modelingmentioning

confidence: 99%

See 1 more Smart Citation

Human-State-Aware Controller for a Tethered Aerial Robot Guiding a Human by Physical Interaction

Allenspach

Vyas

Rubio

et al. 2022

IEEE Robot. Autom. Lett.

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With the rapid development of Aerial Physical Interaction, the possibility to have aerial robots physically interacting with humans is attracting a growing interest. In one of our previous works [1], we considered one of the first systems in which a human is physically connected to an aerial vehicle by a cable. There, we developed a compliant controller that allows the robot to pull the human toward a desired position using forces only as an indirect communication-channel. However, this controller is based on the robot-state only, which makes the system not adaptable to the human behavior, and in particular to their walking speed. This reduces the effectiveness and comfort of the guidance when the human is still far from the desired point. In this paper, we formally analyze the problem and propose a human-state-aware controller that includes a human's velocity feedback. We theoretically prove and experimentally show that this method provides a more consistent guiding force which enhances the guiding experience.

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Section: Modelingmentioning

confidence: 99%

“…Motivated by scientific challenges, as well as industrial and economical potentials, the robotics community is conceiving and studying new aerial robots able to interact with and manipulate the environment [2]. Those go from new multi-rotor platforms that are fully-, omni-, and over-actuated [3], to recent aerial manipulator [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Human-State-Aware Controller for a Tethered Aerial Robot Guiding a Human by Physical Interaction

Allenspach

Vyas

Rubio

et al. 2022

IEEE Robot. Autom. Lett.

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“…The increased controllable DOF means that with proper input allocation, the multi-rotor vehicles can have enhanced control over their motion [27], which offers the redundancy of manipulating a payload or interacting with the environment and adds up to the versatility of the vehicle. [1], [12] show that by attaching quadrotors rigidly on objects can the group of quadrotors cooperatively track the objects along a trajectory.…”

Section: Related Workmentioning

confidence: 99%

Modular Multi-Rotors: From Quadrotors to Fully-Actuated Aerial Vehicles

Xu¹,

D’Antonio²,

Saldaña³

2022

Preprint

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Traditional aerial vehicles have specific characteristics to perform specific tasks. For instance, in aerial transportation, the vehicles are limited with a maximum payload that cannot be extended to transport heavier objects. We propose a versatile modular robotic system that can increase its payload and controllable degrees of freedom by reconfiguring heterogeneous modules; we call it H-ModQuad. The system consists of cuboid modules, propelled by quadrotors with tilted propellers that can generate forces in different directions. We present two module designs with different actuation properties that enhance the capabilities of the assembled robot. By assembling different types of modules, H-ModQuad can increase its controllable degrees of freedom from 4 to 5 and 6 depending on its configuration. We model the modular vehicle and propose a general control strategy for all possible numbers of controllable degrees of freedom. We extend the concept of the actuation ellipsoid to find the best reference orientation that can maximize the performance of the structure. Our approach is validated with experiments using actual robots, showing that the structure can perform independent actuation for rotation and translation.

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“…In an effort towards enhancing manipulation capabilities of aerial robots, the problem has been addressed from different aspects, including the design of new control methods and new platforms more suited for interaction tasks. Those solutions lead to a new generation of aerial manipulators based on fully actuated, multi-, and omnidirectional thrust vehicles [2], capable to generate forces and torques in 6 degrees of freedom (DOF), and equipped with interaction tools like rigid rods [3], and articulated arms [4].…”

Section: Introductionmentioning

confidence: 99%

Energy Tank-Based Policies for Robust Aerial Physical Interaction with Moving Objects

Brunner¹,

Livio²,

Siegwart³

et al. 2022

Preprint

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Although manipulation capabilities of aerial robots greatly improved in the last decade, only few works addressed the problem of aerial physical interaction with dynamic environments, proposing strongly model-based approaches. However, in real scenarios, modeling the environment with high accuracy is often impossible. In this work we aim at developing a control framework for Omnidirectional Micro Aerial Vehicles (OMAVs) for reliable physical interaction tasks with articulated and movable objects in the presence of possibly unforeseen disturbances, and without relying on an accurate model of the environment. Inspired by previous applications of energy-based controllers for physical interaction, we propose a passivity-based impedance and wrench tracking controller in combination with a momentum-based wrench estimator. This is combined with an energy-tank framework to guarantee the stability of the system, while energy and power flow-based adaptation policies are deployed to enable safe interaction with any type of passive environment. The control framework provides formal guarantees of stability, which is validated in practice considering the challenging task of pushing a cart of unknown mass, moving on a surface of unknown friction, as well as subjected to unknown disturbances. For this scenario, we present, evaluate and discuss three different policies.

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Design of multirotor aerial vehicles: A taxonomy based on input allocation

Cited by 71 publications

References 97 publications

Human-State-Aware Controller for a Tethered Aerial Robot Guiding a Human by Physical Interaction

Human-State-Aware Controller for a Tethered Aerial Robot Guiding a Human by Physical Interaction

Modular Multi-Rotors: From Quadrotors to Fully-Actuated Aerial Vehicles

Energy Tank-Based Policies for Robust Aerial Physical Interaction with Moving Objects

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