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: 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: 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: An admittance control method, a robot, and a storage medium are provided. The method includes: obtaining, based on a first admittance controller transfer function between force and position, a desired position of a robot in a current control cycle; determining a corresponding Jacobian matrix according to a configuration of the robot in the current control cycle, and calculating an ill condition number of the Jacobian matrix; and controlling the robot to move by inputting the obtained desired position in the current control cycle to a corresponding joint, in response to the ill condition number being less than a preset maximum ill condition number. In this manner, the configuration of the robot can be maintained within a reasonable rang of the ill condition number, and singularities caused by the admittance controller exceeding the work space can be avoided while the velocity reachability and force reachability of the robot can be ensured.

Abstract: A robot autonomous operation method, a robot, and a computer-readable storage medium are provided. The method includes: moving the robot, under a control of a user, along a guide path in an operation scene; generating a map including the guide path by positioning and mapping during the robot being moved along the guide path in the operation scene; generating a plurality of operation points on the guide path in the map; generating an operation path, wherein the operation path passes through all of the unpassed operation points and has a shortest total distance; and moving the robot, according to the operation path, to each of the unpassed operation points so as to perform an operation. In this manner, it controls the robot to explore the guide path in the operation scene by manual guiding, which can improve the exploration efficiency and reduce the risk of exploring unknown operation scenes.

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: 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: 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 robot control method, a legged robot using the same, and a computer-readable storage medium are provided. The method includes: obtaining a motion parameter of a driving mechanism of a target part of the robot; and obtaining an end pose of the target part by processing the motion parameter of the driving mechanism according to a preset forward kinematics solving model, where the forward kinematics solving model is a neural network model trained by a preset training sample set constructed according to a preset inverse kinematics function relationship. In this manner, a complex forward kinematics solving process can be transformed into a relatively simple inverse kinematics solving process and neural network model processing process, which reduces the computational complexity, shortens the computational time, thereby meeting the demand for real-time control of the robot.

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 robot step length control method, a robot controller, and a computer-readable storage medium are provided. The method includes: if it detects that a humanoid robot is not in a balanced state at a current time, it correspondingly obtains a torso deflection posture parameter, a lower limb parameter and a leg swing frequency of the legs of the humanoid robot at the current time; and it calculates, using a swinging leg capture point algorithm, a calculated step length for maintaining a stable state of the humanoid robot that meets a posture balance requirement of the robot at the current time based on the torso deflection posture parameter, the lower limb parameter, and the leg swing frequency, so that the humanoid robot can be restored to the balanced state after moving with the calculated step length, thereby improving the anti-interference ability of the robot.

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: A robot calibration method, a robot, and a computer-readable storage medium are provided. The method includes: obtaining operation space information of the execution end of the robot; obtaining operation space points after gridding an operation space of the robot by gridding the operation space based on the operation space information; obtaining calibration data by controlling the execution end to move to the operation space points meeting a preset requirement; and calibrating the hand and the image detection device of the robot based on the obtained calibration data. In this manner, the operation space points are determined by gridding the operation space based on the operation space information, and the execution end can be automatically controlled to move to the operation space points that meet the preset requirements so as to obtain the calibration data in an automatic and accurate manner, thereby simplifying the calibration process and improving the efficiency.

Abstract: A robotic arm angle interval inverse solving method and a robotic arm using the same are provided. The method includes: obtaining a joint angle calculation model and a differential relationship model of a target joint of the robotic arm; obtaining extreme arm angles corresponding to a joint angle of the differential relationship model at extreme values based on the differential relationship model; obtaining a joint arm angle interval corresponding to the target joint based on the extreme arm angle and the joint angle calculation model; and obtaining a target arm angle interval corresponding to the robotic arm based on the joint arm angle interval corresponding to the target joint of the robotic arm. In comparison with the existing method to solve the arm angle interval of the robotic arm, a more accurate arm angle interval can be obtained.

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: A center of mass (COM) planning method includes: obtaining a planning position of the COM and a planning speed of the COM of a robot, and calculating a planning capture point of the robot according to the planning position of the COM and the planning speed of the COM; obtaining a measured position of the COM and a measured speed of the COM, and calculating a measured capture point of the robot according to the measured position the measured speed; calculating a desired zero moment point (ZMP) of the robot based on the planning capture point and the measured capture point; obtaining a measured ZMP of the robot, and calculating an amount of change in a position of the COM according to the desired ZMP and the measured ZMP; and correcting the planning position of the COM according to the amount of change in the position of the COM.

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.