Abstract: A control method and a control system using the same as are provided. The method includes: extracting a corresponding component data from a component data stream based on an application protocol registered by each of a plurality of applications and encapsulating a corresponding application data packet for the application in response to receiving the component data stream in a current control period; transmitting the corresponding application data packet to each of the applications; obtaining control data reported by each of the applications according to data reporting timing corresponding to the application; and generating a component control instruction for controlling each of the components according to the control data reported by each of the applications in the current control period and the application protocol registered by the application. In this manner, the orderly control of a smart devices within a limited control period can be achieved.

Abstract: A hip joint mechanism includes: a hip joint frame; an upper leg movably connected to the hip joint frame; a hip actuator configured to drive the hip joint frame to rotate; two upper leg actuators mounted on the hip joint frame; two transmission mechanisms configured to transmit motion from the two upper leg actuators to the upper leg, wherein each of the upper leg actuators comprises a casing connected to the hip joint frame, and an output shaft connected to one corresponding transmission mechanism, each of the two transmission mechanisms comprises an output end; and three connecting mechanisms, wherein the output ends and the hip joint frame are movably connected to the upper leg through the three connecting mechanisms, the three connecting mechanisms are arranged at three vertices of a triangle.

Abstract: The present disclosure provides action imitation method as well as a robot and a computer readable storage medium using the same. The method includes: collecting at least a two-dimensional image of a to-be-imitated object; obtaining two-dimensional coordinates of each key point of the to-be-imitated object in the two-dimensional image and a pairing relationship between the key points of the to-be-imitated object; converting the two-dimensional coordinates of the key points of the to-be-imitated object in the two-dimensional image into space three-dimensional coordinates corresponding to the key points of the to-be-imitated object through a pre-trained first neural network model, and generating an action control instruction of a robot based on the space three-dimensional coordinates corresponding to the key points of the to-be-imitated object and the pairing relationship between the key points, where the action control instruction is for controlling the robot to imitate an action of the to-be-imitated object.

Abstract: A motion control method, a robot controller, and a computer readable storage medium are provided. The method includes: calculating an inverse Jacobian matrix of a whole-body generalized coordinate vector at a current time relative to an actual task space vector of a humanoid robot; calculating a target generalized coordinate vector corresponding to a to-be-executed task space vector at a current moment by combining an actual task space vector and the to-be-executed task space vector into a null space of the inverse Jacobian matrix according to preset position constraint(s) corresponding to the whole-body generalized coordinate vector; and controlling a motion state of the humanoid robot according to the target generalized coordinate vector. In this manner, the motion of the humanoid robot is optimized as a whole to achieve the purpose of controlling the humanoid robot to avoid the limits of the motion of joints.

Abstract: The present disclosure discloses a context-based multi-turn dialogue method.

Abstract: An object detection model generation method as well as an electronic device and a computer readable storage medium using the same are provided. The method includes: during the iterative training of the to-be-trained object detection model, the detection accuracy of the iteration nodes of the object detection model is sequentially determined according to the node order, and the mis-detected negative samples of the object detection model at the iteration nodes with the detection accuracy less than or equal to a preset threshold are enhanced. Then the object detection model is trained at the iteration node based on the enhanced negative samples and a first amount of preset training samples. After the training at the iteration nodes are completed, it returns to the step of sequentially determining the detection accuracy of the iteration nodes of the object detection model until the training of the object detection model is completed.

Abstract: A gait planning method and a robot using the same as well as a computer readable storage medium are provided. The method includes: determining a reference leg length l0 and a leg length variation range A of a robot; performing a trajectory planning on a length of at least one of the legs of the robot using; an equation including the reference leg length, the leg length variation range, and a preset recurrent excitation function of a time variable t. In this manner, the trajectory planning for the leg length of the robot during motion is performed according to the characteristics of motion scene such as robot jumping or running so that the change of the leg length of the robot is adapted to the motion process, which greatly improves the stability of the robot in the motion scene such as jumping or running.

Abstract: A robot control method includes: acquiring distances between a center of mass (COM) of the biped robot and each of preset key points of feet of the biped robot, and acquiring an initial position of the COM of the biped robot; calculating a position offset of the COM based on the distances; adjusting the initial position of the COM based on the position offset of the COM to obtain a desired position of the COM of the biped robot; and determining desired walking parameters of the biped robot based on the desired position of the COM by using a preset inverse kinematics algorithm, wherein the desired walking parameters are configured to control the biped robot to walk.

Abstract: An identification (ID) number setting method for a modular device that comprises a master building element and a plurality of slave building elements that are connected to the master building element, includes: disconnecting the slave building elements from the master building element; setting ID numbers of all of the slave building elements to be a preset ID number; and assigning new ID numbers to slave building elements of N tiers that are connected to one output interface of the master building element in an order from first tier to Nth tier, wherein the slave building elements of the first tier are slave building elements that are directly connected to the output interface, the slave building elements of the Nth tier are slave building elements that are indirectly connected to the output interface through slave building elements of a (N?1)th tier, N is a natural number greater than 1.

Abstract: A humanoid robot control method, a mobile machine using the same, and a computer readable storage medium are provided. The method includes: mapping posture information of leg joints of a human body to leg joint servos of a humanoid robot to obtain an expected rotation angle and an expected rotation angular velocity of non-target optimized joint servos of the leg joint servos and an expected rotation angle and an expected rotation angular velocity of target optimized joint servos of the leg joint servos; obtaining an optimization objective function corresponding to the target optimized joint servos of the leg joint servos; optimizing the expected rotation angle and the expected rotation angular velocity of the target optimized joint servos to obtain a corrected expected rotation angle and a corrected expected rotation angular velocity of the target optimized joint servos; and controlling each of the leg joint servos of the humanoid robot.

Abstract: A modular device includes a polyhedral building element having a first type connector and a number of second type connectors; and a main control module comprising a plurality of second type connectors. The first type connector and the second type connectors are disposed on side surfaces of the building element. One of the second type connectors of the main control module is used to magnetically connect with the first type connector of the building element so as to detachably connect the building element to the main control module. The first type connector includes a first detection circuit, and each second type connector includes a second detection circuit.

Abstract: A biped robot gait control method as well as a robot and a computer readable storage medium are provided. During the movement, the system obtains a current supporting pose of a current supporting leg of the biped robot, and calculates a relative pose between the supporting legs based on the current supporting pose and a preset ideal supporting pose of a next step. The system further calculates modified gait parameters of the next step based on the relative pose between the two supporting legs and a joint distance between left and right ankle joints in an initial state of the biped robot when standing. Finally, the system controls the next supporting leg to move according to the modified gait parameters.

Abstract: A method for detecting blurriness of a human face in an image includes: performing a face detection in a target image; when a human face is detected in the target image, cropping the human face from the target image to obtain a face image and inputting the face image to a first neural network model to perform preliminary detection on a blurriness of the human face in the face image to obtain a preliminary detection result; and when the preliminary detection result meets a deep detection condition, inputting the face image to a second neural network model to perform deep detection on the blurriness of the human face in the face image to obtain a deep detection result.

Abstract: A total centroid state estimation method as well as a humanoid robot and a computer readable storage medium using the same are provided. The method includes: obtaining a motion state of each real joint of the humanoid robot and a motion state of its floating base, where the floating base is equivalent to a plurality of sequent-connected virtual joints; calculating a joint position, a centroid position, and a rotation matrix of each link in the world coordinate system in sequence using the chain rule of homogeneous multiplication according to the position of the joint corresponding to the link to solve a Jacobian matrix of the centroid of the link; solving a total centroid Jacobian matrix based on the Jacobian matrix of the centroid of each link and the total mass; and calculating the total centroid velocity based on the total centroid Jacobian matrix and other parameters.

Abstract: An impedance control method as well as a controller and a robot using the same are provided. The method includes: obtaining joint motion information and joint force information in the joint space of a robotic arm and an actual interaction force acting on an end-effector, and calculating actual motion information of the end-effector in the task space based on the joint motion information; calculating a corrected desired trajectory using environment information and a desired end-effector interaction force, and calculating the impedance control torque based on the joint force information, the actual interaction force, the actual motion information, and desired end-effector information including the corrected desired trajectory and determining a compensation torque based on a nonlinear term in a constructed dynamics equation so as to perform a joint torque control on the robotic arm based on the impedance control torque and the compensation torque.

Abstract: The present disclosure provides an action imitation method as well as a robot and a computer readable storage medium using the same. The method includes: collecting a plurality of action images of a to-be-imitated object; processing the action images through a pre-trained convolutional neural network to obtain a position coordinate set of position coordinates of a plurality of key points of each of the action images; calculating a rotational angle of each of the linkages of the to-be-imitated object based on the position coordinate sets of the action images; and controlling a robot to move according to the rotational angle of each of the linkages of the to-be-imitated object. In the above-mentioned manner, the rotational angle of each linkage of the to-be-imitated object can be obtained by just analyzing and processing the images collected by an ordinary camera without the help of high-precision depth camera.

Abstract: An inverse kinematics solving method for redundant robot as well as a redundant robot using the same are provided. The method includes: obtaining an expression of a Jacobian matrix null space of a current configuration of each robotic arm of the redundant robot corresponding to a preset end pose of the robotic arm according to the preset end pose, and obtaining a relation between an angular velocity of the joints of the redundant robot in the Jacobian matrix null space of the current configuration based on the obtained expression; traversing the Jacobian matrix null space using the relation, and building an energy cost function of the redundant robot based on the relation; obtaining a target joint angle of each joint of the redundant robot based on the optimal inverse kinematics solution to transmit to the servo of the joint so as to control the joint.

Abstract: The present disclosure provides a method for controlling an arm of a robot, including obtaining obstacle information relating to the arm of the robot by at least one sensor, obtaining current posture information of the arm of the robot by a least one detector and obtaining an expected posture information of an end-portion of the arm of the robot, determining an expected trajectory of the end-portion of the arm of the robot, determining an expected speed of the end-portion of the arm of the robot in accordance with the expected trajectory of the end-portion, determining a virtual speed of a target point on the arm of the robot, and configuring a target join speed corresponding to a joint of the arm of the robot. Such that the redundant arm of the robot may be configured to prevent from contacting the obstacles in the complex environment while performing corresponding tasks.

Abstract: Human posture determination is disclosed. Human posture is determined by obtaining range image(s) through a range camera, detecting key points of an estimated skeleton of a human in color data of the range image(s) and calculating positions of the detected key points based on depth data of the range image(s), choosing a feature map from a set of predefined feature maps based on the detected key points among a set of predefined key points, obtaining two features of a body of the human corresponding to the chosen feature map based on the positions of the detected key points, and determining a posture of the human according to the two features in the chosen feature map.