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The motion pattern for underwater snake robots and the joint controller are presented in "Joint controller", followed by a description of the experimental setup in "Experimental setup".
In this section we present a general sinusoidal motion pattern for underwater snake robots proposed in [45] and a control law for making the joint angles track the resulting joint reference angles.
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In particular [46], presents preliminary results by investigating the power consumption of different motion patterns for underwater snake robots.
Simulation and experimental results investigating the relationship between the parameters of the gait patterns and the forward velocity for different motion patterns for underwater snake robots were presented.
Both the simulation and experimental results are obtained for the two most common swimming patterns for underwater snake robot locomotion: lateral undulation and eel-like motion patterns.
In particular, in [46], the relationships between the parameters of the gait patterns, the consumed energy, and the forward velocity for different motion patterns for underwater snake robots were investigated.
The derived relationship between the gait pattern parameters and the steady state velocity presented in Proposition 1 provides a useful tool for motion planning and parameter tuning of sinusoidal gait patterns for underwater snake robots.
These rules can be used to choose the parameters of the gait patterns for underwater snake robots to achieve energy efficient motion while reaching the fastest possible forward velocity.
Based on the closed form model which is briefly presented in "A complex model of underwater snake robots", empirical rules are derived in [46] through an extensive simulation study for the relationships between the parameters of the gait patterns, the consumed energy and the forward velocity for different motion patterns for underwater snake robots.
Based on the simulation results, empirical rules for choosing the values for the parameters of the motion gait pattern of underwater snake robots were proposed.
Finally, by integrating QDWD, pattern distinctness, and local contrast, a reliable saliency map for underwater images can be computed and estimated.
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