Abstract
A multi-medium motion capture system based on markers’ visual detection is developed and experimentally demonstrated for monitoring underwater intelligent agents such as fish biology and bionic robot-fish. Considering the refraction effect between air and water, a three-dimensional (3D) reconstruction model is established, which can be utilized to reconstruct the 3D coordinate of markers underwater from 2D data. Furthermore, the process of markers matching is undertaken through the multi-lens fusion perception prediction combined K-Means clustering algorithm. Subsequently, in order to track the marker of being occluded, according to the kinematics information of fish, an improved Kalman filtering algorithm is proposed. Finally, the feasibility and effectiveness of proposed system are verified through experimental results. The main models and methods in this paper can provide a reference and inspiration for measurement of underwater intelligent agents.
Highlights
As a new kind of autonomous underwater vehicle (AUV) combined with propulsion mechanism of fish and robotics, the bionic robot-fish has been widely applied in water quality monitoring, scientific underwater exploration, oceanic supervision and fishery conservation [1,2,3,4], because of several advantages, compared with traditional AUV based on screw propeller, such as low energy consumption, low noise, high propulsion efficiency and high mobility [5]
Sci. 2020, 10, 6237 the actual fish locomotion data, Yan measured the fish swimming modes by camera set up in the upper area of the water tank and five colored markers attached to the fish body from tail to head, and the motion data will be derived from the five markers data [13]
In order to explore the locomotion patterns and swimming modes of fish for improving the swimming performance of bionic robot-fish, a multi-medium motion capture system based on markers is developed in this paper
Summary
As a new kind of autonomous underwater vehicle (AUV) combined with propulsion mechanism of fish and robotics, the bionic robot-fish has been widely applied in water quality monitoring, scientific underwater exploration, oceanic supervision and fishery conservation [1,2,3,4], because of several advantages, compared with traditional AUV based on screw propeller, such as low energy consumption, low noise, high propulsion efficiency and high mobility [5]. Sci. 2020, 10, 6237 the actual fish locomotion data, Yan measured the fish swimming modes by camera set up in the upper area of the water tank and five colored markers attached to the fish body from tail to head, and the motion data will be derived from the five markers data [13]. Oya reconstructed the 3D information from 2D images captured by two cameras based on the principle of triangulation [18] These studies show that vision-based approaches can be easy to design and quick to implement for reconstructing the 3D motion data of fish. We develop a multi-markers-based motion capture system of fish considering the refraction effect, where eight cameras are set up to simultaneously shoot the markers from different angles for reconstructing the 3D space information of fish movement.
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