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公开(公告)号：US11208186B2
公开(公告)日：2021-12-28
申请号：US17279099
申请日：2020-04-16
Inventor： Junzhi Yu , Zhengxing Wu , Di Chen , Min Tan
Abstract: A water-air amphibious cross-medium bio-robotic flying fish includes a body, pitching pectoral fins, variable-structure pectoral fins, a caudal propulsion module, a sensor module and a controller. The caudal propulsion module is controlled to achieve underwater fish-like body-caudal fin (BCF) propulsion, and the variable-structure pectoral fins is adjusted to achieve air gliding and fast splash-down diving motions of the bio-robotic flying fish. The coordination between the caudal propulsion module and the pitching pectoral fins is controlled to achieve the motion of leaping out of water during water-air cross-medium transition. The ambient environment is detected by the sensor module, and the motion mode of the bio-robotic flying fish is controlled by the controller.
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12.发明授权公开(公告)号：US10962976B1
公开(公告)日：2021-03-30
申请号：US17094820
申请日：2020-11-11
Inventor： Zhengxing Wu , Junzhi Yu , Shuaizheng Yan , Jian Wang , Min Tan
Abstract: A motion control method and system for a biomimetic robotic fish based on an adversarial structured control, includes: taking the accuracy and speed of motion to the target point as a reward term, and taking a power sum of servomotors as a loss term to construct an optimization objective function; optimizing parameters of a central pattern generator model that generates a global control quantity of a servomotor, after curing its parameters, optimizing the parameters of the servomotor compensation control model; iteratively optimizing the parameters of the model; obtaining the global control signal and compensation control signal of the biomimetic robotic fish through the trained model, and using the linear combination of the two sets of output signals as the control signal of the servomotor of the robotic fish to realize the motion control of the fish.
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公开(公告)号：US10935986B1
公开(公告)日：2021-03-02
申请号：US17069868
申请日：2020-10-14
Inventor： Junzhi Yu , Zhengxing Wu , Jian Wang , Shuaizheng Yan , Min Tan
Abstract: A gliding depth control method for a biomimetic gliding robotic dolphin includes: obtaining a preset gliding depth and a preset yaw angle; obtaining an estimated velocity by a sliding mode observer based on depth information and inertial navigation information, and obtaining a control quantity of pectoral fins on both sides of the biomimetic gliding robotic dolphin by a yaw controller in combination with the preset yaw angle; obtaining a segmented diving velocity reference trajectory by constructing and segmenting a Bézier curve; obtaining a diving control quantity by a model predictive control method in combination with the estimated velocity; obtaining a target position of a piston through a buoyancy principle, and obtaining a control quantity of the piston according to a current position of the piston; and controlling the biomimetic gliding robotic dolphin to glide based on the control quantity of the piston and the control quantity of the pectoral fins.
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公开(公告)号：US09886775B2
公开(公告)日：2018-02-06
申请号：US15306980
申请日：2014-04-28
Inventor： Zhiqiang Cao , Xilong Liu , Chao Zhou , Min Tan , Kun Ai
CPC classification number: G06T7/60 , G06T7/70 , G06T2207/10004 , G06T2207/20021 , G06T2207/20084 , G06T2207/30244 , G06T2207/30252
Abstract: The disclosure relates to a method for detection of the horizontal and gravity directions of an image, the method comprising: selecting equidistant sampling points in an image at an interval of the radius of the sampling circle of an attention focus detector; placing the center of the sampling circle of the attention focus detector on each of the sampling points, and using the attention focus detector to acquire attention focus coordinates and the corresponding significant orientation angle, and all the attention focus coordinates and the corresponding significant orientation angles constitute a set Ωp; using an orientation perceptron to determine a local orientation angle and a weight at the attention focus according to the gray image information, and generating a local orientation function; obtaining a sum of each of the local orientation functions as an image direction function; obtaining a function MCGCS(β), and further obtaining the horizontal and gravity identification angles.
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