Abstract: A method for estimating a pose of a humanoid robot includes: processing obtained pose parameters of a waist of the humanoid robot and plantar motion parameters of the humanoid robot to obtain the measured pose parameters of a center point of the waist of the humanoid robot; calculating predicted pose parameters of the center point of the waist according to the obtained pose parameters of the waist; and fusing the measured pose parameters and the predicted pose parameters to obtain estimated pose parameters of the center point of the waist.

Abstract: A mask wearing status alarming method, a mobile device, and a computer readable storage medium are provided. The method includes: performing a face detection on an image to determine face areas each including a target determined as a face; determining a mask wearing status of the target in each face area; confirming the mask wearing status of the target in each face area using a trained face confirmation model to remove the face areas comprising the target being mistakenly determined as the face and determining a face pose in each of the remaining face areas to remove the face areas with the face pose not meeting a preset condition, in response to determining the mask wearing status as a not-masked-well status or a unmasked status; and releasing an alert corresponding to the mask wearing status of the target in each of the remaining face areas.

Abstract: The present disclosure provides a robotic arm space position adjustment method, a robotic arm controller, and a computer readable storage medium. The method includes: calculating a potential energy function of moving a feature point of the robotic arm to a reference point based on an obtained preset acceleration of an artificial gravitational field, first vector of the artificial gravitational field in a preset reference coordinate system, second vector of the feature point of the robotic arm in the preset reference coordinate system, and a third vector of the reference point in the preset reference coordinate system; and calculating a null space virtual moment of moving the feature point of the robotic arm to the reference point based on a preset null space operator and the potential energy function, so as to adjust each joint of the robotic arm.

Abstract: A method for a multi-legged robot having a body and a number of legs, includes: obtaining a current pose of the body, forces applied to the body, and joint angles of each of supporting legs of the legs; creating a mapping matrix from the forces applied to the body to desired support forces applied to soles of the supporting legs; obtaining priority targets by prioritizing the forces acting in different directions, determining a weight matrix for each priority target, and creating an optimization model of the support forces for each priority target based on the mapping matrix and the weight matrices; solving the optimization model of each of the priority targets to obtain the desired support forces corresponding to each of the priority targets; and calculating joint torques of the supporting legs for joint control, based on the solved desired support forces and Jacobian matrices corresponding to the supporting legs.

Abstract: A leg mechanism of a humanoid robot includes: an upper leg, a lower leg rotatably coupled to the upper leg, a knee module actuator mounted to the upper leg, a foot rotatably connected to the lower leg, a knee transmission mechanism connected to the knee module actuator and the lower leg and configured to transmit rotary motion from the knee module actuator to the lower leg, at least one ankle module actuator mounted to the upper leg, at least one ankle transmission mechanism connected to the at least one ankle module actuator and the foot and configured to transmit rotary motion from the at least one ankle module actuator to the foot.

Abstract: A humanoid robot balance control method, a humanoid robot, and a storage medium are provided. The method includes: obtaining a task equation of each of a plurality of deconstructed tasks in a corresponding control cycle by solving a plurality of deconstructed task models using a relevant actual state and a corresponding expected state of the humanoid robot; calculating an optimal solution of a multi-task error optimization function based on each task equation; and generating a joint control instruction of the corresponding control cycle based on the optimal solution in response to the optimal solution being obtained within the corresponding control cycle so as to control corresponding joint(s) to execute the tasks. In such manner, it can ensure that the robot satisfies the necessary constraints while executing multiple tasks, and also comprehensively considers the errors of all the tasks to ensure the execution of all the tasks.

Abstract: A head mechanism includes a base connectable to a body of a robot, a mounting member arranged above the base, a connecting member rotatably connected to the base and the mounting member. The connecting member, together with the mounting member, is rotatable relative to the base about a first axis, and the mounting member is rotatable relative to the connecting member about a second axis. The first axis and the second axis extend in different directions. The head mechanism further includes two first actuating mechanisms fixed to the base, and the two first actuating mechanisms are configured to drive the mounting member to rotate with respect to the base.

Abstract: A computer-implemented gait planning method includes: determining a pitch angle between a foot of the robot and a support surface where the robot stands; determining a support point on a sole of the foot according to the pitch angle; calculating an ankle-foot position vector according to the support point, wherein the ankle-foot position vector is a position vector from an ankle of the robot to a support point on a sole of the foot; calculating a magnitude of change of an ankle position according to the pitch angle and the ankle-foot position vector; and obtaining a compensated ankle position by compensating the ankle position according to the magnitude of change of the ankle position.

Abstract: A robot control method includes: obtaining force information associated with a left foot and a right foot of the robot; calculating a zero moment point of a COM of a body of the robot based on the force information; updating a motion trajectory of the robot according to the zero moment point of the COM of the body to obtain an updated position of the COM of the body; performing inverse kinematics analysis on the updated position of the COM of the body to obtain joint angles of a left leg and a right leg of the robot; and controlling the robot to move according to the joint angles.

Abstract: A mapping method for a mobile robot includes: obtaining positions of particles corresponding to the mobile robot using a particle filtering approach; selecting one of the particles with a largest weight in a particle swarm corresponding to a current time point, performing position matching between the one of the particles and a historical trajectory formed by the one of the particles with the largest weight, and determining whether the positions of the particles corresponding to the mobile robot match positions of historical trajectory points of the mobile robot; in response to the positions of the particles corresponding to the mobile robot matching the positions of the historical trajectory points of the mobile robot, optimizing a trajectory of the mobile robot using a graph optimization approach; and building a map based on the optimized trajectory.

Abstract: A walking control method for a biped robot includes: detecting whether the biped robot is in an unbalanced state; in response to detection that the biped robot is in the unbalanced state, obtaining a predicted balance step length corresponding to the biped robot in the unbalanced state; performing a smooth transition processing on the predicted balance step length according to a current movement step length of the biped robot to obtain a desired balance step length corresponding to the predicted balance step length; determining a planned leg trajectory of the biped robot according to the desired balance step length; and controlling a current swing leg of the biped robot to move according to the planned leg trajectory.

Abstract: A mechanical arm includes a first link connectable to a surface, a second link, a third link, a fourth link, and a fifth link that are coupled to one another in series, and an end effector connectable to the fifth link. The end effector is rotatable about an axis of rotation same as an axis of rotation of the fourth link, and rotatable about an axis of rotation orthogonal to the axis of rotation of the fourth link. The first link, the second link, the third link, the fourth link, and the fifth link are collectively structured and configured to rotate such that the end effector is actuatable to a workspace under the surface.

Abstract: A collision detection method, a storage medium, and a robot are provided. The method includes: calculating an external torque of a first joint of the robot based on a preset generalized momentum-based disturbance observer; calculating an external torque of a second joint of the robot based on a preset long short-term memory network; calculating an external torque of a third joint of the robot based on the external torque of the first joint and the external torque of the second joint; and determining whether the robot has collided with an external environment or not based on the external torque of the third joint and a preset collision threshold. In the present disclosure, the component of the model error in the joint external torque calculated by the disturbance observer is eliminated to obtain the accurate contact torque, thereby improving the accuracy of the collision detection.

Abstract: A robot stability control method includes: obtaining a desired zero moment point (ZMP) and a fed-back actual ZMP of a robot at a current moment; based on a ZMP tracking control model, the desired ZMP and the actual ZMP, calculating a desired value of a motion state of a center of mass of the robot at the current moment, wherein the desired value of the motion state of the center of mass comprises a correction amount of the position of the center of mass; based on a spring-mass-damping-acceleration model and the desired value of the motion state of the center of mass, calculating a lead control input amount for the correction amount of the position of the center of mass; and controlling motion of the robot according to the lead control input amount and a planned value of the position of the center of mass at the current moment.

Abstract: A method of controlling a robot includes: obtaining an inertia matrix and a slack variable of the robot, and determining a momentum equation of the robot according to the inertia matrix and the slack variable; obtaining reference joint angles corresponding to a reference action of the robot; determining an optimization objective function of the momentum equation according to a first preset weight coefficient of the slack variable and a second preset weight coefficient of the reference joint angles; and determining joint angles of the robot according to the optimization objective function, and driving the robot to move according to the joint angles of the robot.

Abstract: A motion terrain determining method, a robot, and a computer-readable storage medium are provided. The method includes: determining each sine parameter and each cosine parameter corresponding to a target joint in a plurality of joints of the robot according to one or more constraint conditions; determining a motion trajectory of the robot according to the sine parameter and the cosine parameter corresponding to the target joint; and determining a motion terrain of the robot according to the motion trajectory. In this manner, the best motion terrain can be obtained, and the robot is controlled to move on the determined motion terrain when determining the dynamics parameters of the robot, where the obtained dynamics parameters are more accurate to effectively improve the efficiency of the identification of the dynamics parameters.

Abstract: A jumping motion control method for a biped robot includes: before feet of the biped robot leaves a support surface, estimating a motion trajectory of the biped robot that leaves the support surface according to a period of time when the biped robot stays or flips in the air; calculating a first motion angle of each joint of legs of the biped robot according to the motion trajectory and inverse kinematics; determining a constraint condition according to a motion type to which an action to be performed by the biped robot corresponds; optimizing the first motion angles according to the constraint condition to obtain a second motion angle of each joint of legs of the biped robot; and controlling a jumping motion of the biped robot according to the second motion angles.

Abstract: A robot control method, a robot, and a computer-readable storage medium are provided. The method includes: obtaining a linear motion model of a robot; determining a predicted state corresponding to each moment in a preset time period based on the linear motion model; determining an expected state corresponding to each moment in the preset time period; and determining a compensation value of a velocity of joint(s) at each moment from k-th moment to k+N?1-th moment based on the predicted state corresponding to each moment in the preset time period and the expected state corresponding to each moment in the preset time period, determining instruction parameter(s) at the k-th moment based on the compensation value of the velocity of the joint(s) at the k-th moment, and adjusting a position of each of the joint(s) of the robot according to the instruction parameter(s) at the k-th moment.

Abstract: A robot obstacle avoidance method, a robot controller using the same, and a storage medium are provided. The method includes: determining an influence value of an obstacle on a motion range of a joint of the robot according to a position of the obstacle in a workspace of the robot; establishing a state transition relationship of the robot by taking a joint velocity of the robot as a control target and a joint angular velocity of the robot as a control input quantity; and avoiding the robot from colliding with the obstacle during a movement process of the robot by performing a model predictive control on the robot according to the state transition relationship and the influence value. In the present disclosure, the influence of the obstacle on the motion range of the joint of the robot is fully considered.

Abstract: A direct force feedback control method as well as a controller and a robot using the same are provided. The method includes: obtaining an actual position and an actual speed of an end of the robotic arm and an actual external force acting on the end in a Cartesian space; calculating an impedance control component of the end in the Cartesian space based on the obtained actual position, the obtained actual speed, the obtained actual external force, an expected position, an expected speed, and an expected acceleration of the end; calculating a force control component of the end in the Cartesian space based on an expected interaction force acting on the end, the actual external force, and the actual speed; determining whether the actual external force is larger than a preset threshold, and obtaining a total force control quantity of the end of the robotic arm in the Cartesian space.