Catenary-based visual servoing for tether shape control between underwater vehicles

Laranjeira, Matheus; Dune, Claire; Hugel, Vincent

doi:10.1016/j.oceaneng.2020.107018

Cited by 36 publications

(30 citation statements)

References 39 publications

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“…It also suggests that a longer tether between robots does not necessarily correspond to better efficiency. This finding may impact prior arts wherein the length is not considered [4,14] or is fixed [5,6,17,18,31].…”

Section: B Trajectory Trackingmentioning

confidence: 99%

“…Several setups have showcased the ability to handle flexible connections in diverse scenarios among robots. For instance, a dual-arm robot manipulates rope-like objects in clutter [15], three quadcopters connected by a net catch and throw a ball [11], multiple robots manipulate deformable bed sheet [16], a visual servoing scheme maintains the tether's shape between two-wheel robots [17,18], and a pair of tethered quadcopters move an object using the tether [6,7]. Although the above literature strongly suggests the significance of maintaining tether/net shapes in cooperative planning, directly and precisely controlling its shape is oftentimes unnecessary, resulting in increased complexity in both modeling and control.…”

Section: A Related Workmentioning

confidence: 99%

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Object Gathering with a Tethered Robot Duo

Su,

Jiang,

Zhu

et al. 2022

Preprint

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We devise a cooperative planning framework to generate optimal trajectories for a robot duo tethered by a flexible net to gather scattered objects spread in a large area. Specifically, the proposed planning framework first produces a set of dense waypoints for each robot, serving as the initialization for optimization. Next, we formulate an iterative optimization scheme to generate smooth and collision-free trajectories while ensuring cooperation within the robot duo to gather objects efficiently and avoid obstacles properly. We validate the generated trajectories in simulation and implement them in physical robots using Model Reference Adaptive Controller (MRAC) to handle unknown dynamics of carried payloads. In a series of studies, we find that: (i) a U-shape cost function for maintaining separation distance is effective in planning cooperative robot duo, and (ii) the task efficiency is not always proportional to the tethered net's length. Given an environment configuration, our framework can gauge the optimal net length. To our best knowledge, ours is the first that provides such estimation for tethered robot duo.

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Section: B Trajectory Trackingmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Object Gathering with a Tethered Robot Duo

Su,

Jiang,

Zhu

et al. 2022

Preprint

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“…Thus, computer vision is a sensing part of the robotic system that provides feedback on the state of the environment. Visual servoing has been receiving several contributions over the last three decades, with proposals that range from very simple tasks to advanced manipulation of objects (ALLIBERT et al, 2019, LARANJEIRA, DUNE & HUGEL, 2020, PARADIS et al, 2021.…”

Section: Introductionmentioning

confidence: 99%

Assembly and testing of a pan-tilt camera mechanism for robotics visual servoing applications / Montagem e teste de um mecanismo com câmera pan-tilt para aplicações de servovisão robótica

Mil-Homens¹,

Zachi²

2022

BJDV

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This work is about the assembling and testing of a camera on a PAN-TILT mechanism. The prototype is also composed of two direct current (DC) motors with gearboxes, fixed to the mechanism's rotation axes. The function of the motors is to provide the necessary torques to rotate the motion axes and provide a desired orientation for the camera. The ultimate goal is to obtain a fully functional mechanism to serve as a test bench for robotics visual servoing applications and for testing future control algorithms.

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“…For shape servoing, commonly selected features are curvatures (Navarro-Alarcon et al, 2014), points (Wang et al) and angles . Laranjeira et al proposed a catenary-based feature for tethered management on wheeled and underwater robots (Laranjeira et al, 2017(Laranjeira et al, , 2020. A more general feature vector is that containing the Fourier coefficients of the object contour (Navarro-Alarcon and Liu, 2018;Zhu et al, 2018).…”

Section: Introductionmentioning

confidence: 99%