Image-based control for dynamically cross-coupled aerial manipulation

In this letter, a hybrid visual servoing with a hierarchical task-composition control framework is described for aerial manipulation, i.e., for the control of an aerial vehicle endowed with a robot arm. The proposed approach suitably combines into a unique hybrid-control framework the main benefits of both image-based and position-based control schemes. Moreover, the underactuation of the aerial vehicle has been explicitly taken into account in a general formulation, together with a dynamic smooth activation mechanism. Both simulation case studies and experiments are presented to demonstrate the performance of the proposed techniqu

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“…The target object is a bar endowed with two visual markers at the ends. A UAM velocity control has also been employed [17], [18].…”

Section: Simulation Resultsmentioning

confidence: 99%

Hybrid Visual Servoing With Hierarchical Task Composition for Aerial Manipulation

Lippiello

Cacace

Santamaria-Navarro

et al. 2016

IEEE Robot. Autom. Lett.

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“…The grasping object is a bar with two visual markers attached at the two ends. A low-level velocity control of the whole system has also been employed [13], [14], [20], [21].…”

Section: Simulation Resultsmentioning

confidence: 99%

Hybrid visual servoing for aerial grasping with hierarchical task-priority control

Buonocore

Cacace

Lippiello

2015

2015 23rd Mediterranean Conference on Control and Automation (MED)

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In this paper a hybrid visual servoing with a dynamic and hierarchical task-priority control framework is proposed for the control of an aerial vehicle endowed with a robot arm. The proposed task composition algorithm retains the main benefits of classical image-based and position-based control scheme, that can be suitably combined in a common hybridcontrol framework. Moreover, the under-actuation of the vehicle base has been systematically taken into account within a general formulation, while a dynamic smooth activation/deactivation mechanism is proposed to avoid discontinuity in the control action. Simulations have been proposed to demonstrate the effectiveness of the proposed approach.

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“…The use of vision for the execution of aerial robotic tasks is a widely adopted solution to cope with unknown environments. In Mebarki et al, 2014;Mebarki and Lippiello, 2014a] new image-based control laws are presented to automatically position UAM parts on target structures, where the system redundancy and underactuation of the vehicle base are explicitly taken into account. The camera is attached on the aerial platform and the positions of both the arm end effector and the target are projected onto the image plane in order to perform an image-based error decrease.…”

Section: Related Workmentioning

confidence: 99%

“…When projecting the end effector, both end effector and vehicle velocities are required to be known, which for the second case creates a dependency on the robot odometry estimator that rarely achieves the required precision for aerial manipulation in a real scenario (e.g., without motion capture systems). Moreover, in both [Mebarki and Lippiello, 2014a] and [Mebarki et al, 2014] the proposed control schemes are only validated in simulation.…”

Section: Related Workmentioning

confidence: 99%

“…The target object is a bar with two visual markers at the ends, used to obtain the position and orientation of the target object with respect to the camera. To drive the UAM, we employed a velocity control as in [Mebarki et al, 2014;Mebarki and Lippiello, 2014b]. Video 4 in Appendix C reports real experiments with grasping and pluggin maneuvers using this hierarchical control law.…”

Section: Htpc Using Full Least Squaresmentioning

confidence: 99%

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Visual Guidance of Unmanned Aerial Manipulators

Santamaria-Navarro

Solà

Andrade‐Cetto

2019

Springer Tracts in Advanced Robotics

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The ability to fly has greatly expanded the possibilities for robots to perform surveillance, inspection or map generation tasks. Yet it was only in recent years that research in aerial robotics was mature enough to allow active interactions with the environment. The robots responsible for these interactions are called aerial manipulators and usually combine a multirotor platform and one or more robotic arms. The main objective of this thesis is to formalize the concept of aerial manipulator and present guidance methods, using visual information, to provide them with autonomous functionalities. A key competence to control an aerial manipulator is the ability to localize it in the environment. Traditionally, this localization has required external infrastructure of sensors (e.g., GPS or IR cameras), restricting the real applications. Furthermore, localization methods with on-board sensors, exported from other robotics fields such as simultaneous localization and mapping (SLAM), require large computational units becoming a handicap in vehicles where size, load, and power consumption are important restrictions. In this regard, this thesis proposes a method to estimate the state of the vehicle (i.e., position, orientation, velocity and acceleration) by means of on-board, low-cost, lightweight and high-rate sensors. With the physical complexity of these robots, it is required to use advanced control techniques during navigation. Thanks to their redundancy on degrees-of-freedom, they offer the possibility to accomplish not only with mobility requirements but with other tasks simultaneously and hierarchically, prioritizing them depending on their impact to the overall mission success. In this work we present such control laws and define a number of these tasks to drive the vehicle using visual information, guarantee the robot integrity during flight, and improve the platform stability or increase arm operability. The main contributions of this research work are threefold: (1) Present a localization technique to allow autonomous navigation, this method is specifically designed for aerial platforms with size, load and computational burden restrictions. (2) Obtain control commands to drive the vehicle using visual information (visual servo). (3) Integrate the visual servo commands into a hierarchical control law by exploiting the redundancy of the robot to accomplish secondary tasks during flight. These tasks are specific for aerial manipulators and they are also provided. All the techniques presented in this document have been validated throughout extensive experimentation with real robotic platforms. i

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Image-based control for dynamically cross-coupled aerial manipulation

Cited by 16 publications

References 18 publications

Hybrid Visual Servoing With Hierarchical Task Composition for Aerial Manipulation

Hybrid Visual Servoing With Hierarchical Task Composition for Aerial Manipulation

Hybrid visual servoing for aerial grasping with hierarchical task-priority control

Visual Guidance of Unmanned Aerial Manipulators

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