ACMarker: Acoustic Camera-Based Fiducial Marker System in Underwater Environment

Wang, Yusheng; Ji, Yonghoon; Liu, Dingyu; Tamura, Yusuke; Yamashita, Atsushi; Asama, Hajime

doi:10.1109/lra.2020.3005375

Cited by 14 publications

(2 citation statements)

References 22 publications

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“…In natural underwater scenarios, features are sparse. The proposed feature matching method uses low-cost chessboard markers, which are easier to make and obtain compared to specially designed three-dimensional markers [ 34 , 35 ]. The proposed marker-assisted feature-enhanced matching method avoids time-consuming and laborious underwater scene setting and provides the feature point pairs needed for image stitching in a cost-effective manner.…”

Section: Binocular Visual Field Stitching For Fish-like Vision Systemmentioning

confidence: 99%

A Fish-like Binocular Vision System for Underwater Perception of Robotic Fish

Tong,

Wu,

Wang

et al. 2024

Biomimetics

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Biological fish exhibit a remarkably broad-spectrum visual perception capability. Inspired by the eye arrangement of biological fish, we design a fish-like binocular vision system, thereby endowing underwater bionic robots with an exceptionally broad visual perception capacity. Firstly, based on the design principles of binocular visual field overlap and tangency to streamlined shapes, a fish-like vision system is developed for underwater robots, enabling wide-field underwater perception without a waterproof cover. Secondly, addressing the significant distortion and parallax of the vision system, a visual field stitching algorithm is proposed to merge the binocular fields of view and obtain a complete perception image. Thirdly, an orientation alignment method is proposed that draws scales for yaw and pitch angles in the stitched images to provide a reference for the orientation of objects of interest within the field of view. Finally, underwater experiments evaluate the perception capabilities of the fish-like vision system, confirming the effectiveness of the visual field stitching algorithm and the orientation alignment method. The results show that the constructed vision system, when used underwater, achieves a horizontal field of view of 306.56°. The conducted work advances the visual perception capabilities of underwater robots and presents a novel approach to and insight for fish-inspired visual systems.

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Section: Binocular Visual Field Stitching For Fish-like Vision Systemmentioning

confidence: 99%

A Fish-like Binocular Vision System for Underwater Perception of Robotic Fish

Tong,

Wu,

Wang

et al. 2024

Biomimetics

View full text Add to dashboard Cite

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“…For the base station system, the popular Ultra-Wide Band (UWB) technology can achieve positioning accuracy within ten centimeters at a low cost [12], but the lack of orientation measurement and the sensitivity to metal surfaces limit its use [7]. The fiducial marker system achieves centimeter-level localization accuracy robustly at the cost of just a camera and several printed papers, making it the choice of many robotic researchers [13], [14]. There has been sufficient research on the design, detection, and decoding processes of visual fiducial markers, such as ARTag [15], ArUco 3 [16], and AprilTag 3 [17].…”

Section: Related Workmentioning

confidence: 99%

Indoor Localization for Quadrotors using Invisible Projected Tags

Li¹,

Liu²,

Zhang³

2022

Preprint

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Augmented reality (AR) technology has been introduced into the robotics field to narrow the visual gap between indoor and outdoor environments. However, without signals from satellite navigation systems, flight experiments in these indoor AR scenarios need other accurate localization approaches. This work proposes a real-time centimeter-level indoor localization method based on psycho-visually invisible projected tags (IPT), requiring a projector as the sender and quadrotors with high-speed cameras as the receiver. The method includes a modulation process for the sender, as well as demodulation and pose estimation steps for the receiver, where screen-camera communication technology is applied to hide fiducial tags using human vision property. Experiments have demonstrated that IPT can achieve accuracy within ten centimeters and a speed of about ten FPS. Compared with other localization methods for AR robotics platforms, IPT is affordable by using only a projector and high-speed cameras as hardware consumption and convenient by omitting a coordinate alignment step. To the authors' best knowledge, this is the first time screen-camera communication is utilized for AR robot localization.

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