14 results about "Zero moment point" patented technology

The invention relates to a robot standing posture recovery method and device, equipment, a storage medium and a product, and the method comprises the following steps: after the falling state of a robot is detected, collecting joint angles in real time to obtain falling posture data, and calculating contact points with the ground to determine a support part set; in combination with a preset zero moment point reference trajectory, performing inverse dynamics solution based on the set to generate a joint motion sequence, and configuring the joint motion sequence as joint position instructions to form a getting-up planning trajectory; the current output torque of each joint is compensated in real time according to the track, a driving torque instruction is obtained, each joint motor is driven to execute actions, so that the robot is recovered from the current posture to the standing posture, and the problem that the preset rigid action is often not matched with the current actual supporting state when the robot falls to the ground, and consequently the robot cannot stand up when executing the getting-up action is solved. And center-of-gravity unbalance is easy to occur.

The invention relates to a method and device for a biped robot to wear common sports shoes, and belongs to the technical field of robots. The method comprises the steps that a pre-planned gait track is initialized and generated; calculating the actual centroid position of the robot at each moment; a Kalman filtering algorithm is adopted to fuse multi-source data to update the normal stiffness and the friction coefficient of the sole in real time, and the rate is updated through adaptive gain adjustment parameters; adjusting a zero moment point constraint range, and generating a centroid reference position of a preset step number; establishing a sole characteristic database, training a machine learning model, inputting shoe parameters into the machine learning model, and outputting step length, step frequency and ankle joint rigidity by the machine learning model; an ankle joint target angle and a knee joint target angle are solved through inverse kinematics, and a joint motor is driven in combination with a PD control algorithm and a self-adaptive item; when the vertical acceleration of the IMU sensor is larger than a preset acceleration threshold value, the time period before grounding is judged, and a compliant mode is triggered to control the ankle joint rigidity and the torque borne by the joint.

The application relates to a robot standing posture recovery method, device, equipment, storage medium and product, which comprises the following steps: after detecting a robot falling state, acquiring falling posture data by collecting joint angles in real time, solving contact points with the ground to determine a support part set; combining a preset zero moment point reference track, performing inverse dynamics solving based on the set, generating a joint motion sequence, configuring each joint position instruction to form a standing-up planning track; according to the track, real-time compensation is performed on the current output torque of each joint to obtain a driving torque instruction, and each joint motor is driven to execute an action, so that the robot is recovered from the current posture to the standing posture, and the technical problem that the preset rigid action of the robot when falling often does not match the current actual support state, leading to the robot being prone to center of gravity imbalance when executing the standing-up action is solved.

The aim is to suppress slippage even when horizontal forces are generated in situations where the vertical load is small, such as on the legs far from the robot's center of gravity. [Solution] The control device includes a processor, which, when a six-dimensional vector combining three-dimensional translational force and three-dimensional rotational moment is used as a wrench, determines, based on the relationship between the robot's center of gravity and the ZMP, and the relationship between the ZMP and one or more contact points, a target wrench to be applied to the robot's center of gravity, by distributing it to one or more contact points, and controls the robot's walking according to the determined contact wrench.

A robot control method, comprising: when a robot carries a load, performing foot trajectory planning on the robot, to obtain a foot trajectory planning result of the robot; determining a zero moment point reference trajectory of the robot on the basis of the foot trajectory planning result; determining an equivalent center of mass trajectory on the basis of the zero moment point reference trajectory, wherein an equivalent center of mass is the center of mass of the robot and the load, taken as a whole; determining a center of mass trajectory of the robot on the basis of the equivalent center of mass trajectory; performing inverse kinematics solution on the basis of the center of mass trajectory of the robot, to obtain leg joint poses of the robot; and on the basis of the leg joint poses of the robot, controlling the robot to move. The impact caused by the load is fully considered, thereby effectively improving the walking stability of the robot. Also provided are a robot control apparatus, a computer-readable storage medium, and a robot.

The invention discloses a six-foot robot foot force distribution method based on gradient descent. The six-foot robot foot force distribution method comprises the steps that a hip joint and a foot end contact point are connected to serve as a virtual leg of a robot; solving the coordinate of a zero moment point under the fuselage coordinate system according to a moment balance equation; according to a force and moment balance equation, the function relation between the force borne by the foot end and the ratio between the foot end position and the lateral force borne by the foot end and the tangential force is obtained; according to the transformation matrix, the position of the foot end of the supporting leg in the fuselage coordinate system is obtained, and the function relation between the joint rotation angle and the foot end position is obtained; establishing a target function that the stress of the foot end is roughly uniform in the whole advancing process, calculating foot end coordinates under the condition that the comprehensive stress of the foot end of the supporting leg is uniform and the ratio of the lateral force to the tangential force borne by the foot end based on a gradient descent algorithm, and calculating the force borne by the foot end of the supporting leg. According to the foot force distribution method disclosed by the invention, a plurality of legs which simultaneously touch the ground in one movement period can be uniformly stressed, so that the obtained force borne by each supporting leg is closer to an optimal solution.

This invention discloses a method for online footing point generation and adjustment of a bipedal robot that combines active and passive methods. The method includes: determining the planned zero-moment point trajectory and the planned center-of-mass trajectory; designing a virtual inverted pendulum center-of-mass tracking controller; controlling the desired zero-moment point trajectory to ensure the robot's desired center-of-mass trajectory tracks the actual zero-moment point position and calculates external forces, applying them to the virtual inverted pendulum for state updates; optimizing the desired footing point position based on the estimated center-of-mass trajectory for the next two steps and the planned footing point position through online ankle trajectory tracking control, ensuring the robot's desired ankle position follows the calculated desired joint angle, which is then applied to the bipedal robot. This invention achieves a larger and more flexible footing point adjustment effect while ensuring real-time computation, resulting in better disturbance suppression and balance restoration.

The present application belongs to the technical field of robot control, and more particularly relates to a gait switching control method and system for a legged manipulator robot, which comprises the following steps: calculating the current gait of the legged manipulator robot and the positions of the zero moment points of the gait to be switched; planning a zero moment point reference trajectory for the legged manipulator robot; using a model predictive control algorithm to control the legged manipulator robot to move according to the zero moment point reference trajectory, and adjusting the control parameters of the predictive control algorithm in real time according to a loss function, while outputting a state trajectory and an input trajectory in real time, so as to realize gait switching of the legged manipulator robot. The gait switching control method for the legged manipulator robot provided by the present application fully considers the influence of manipulator dynamics on the motion performance of the whole robot, and can realize gait switching control of the legged robot.

The invention discloses a humanoid robot instep ball picking reinforcement learning control method based on DCM constraint optimization, and the method employs a PPO Lagrangian algorithm, and minimizes the cost generated after the robot picks a ball and falls while guaranteeing the maximization of the total reward, thereby reducing the falling times in the ball picking process of the robot. A motion divergence-external force disturbance-based instability model is designed, a foot falling anti-interference strategy based on DCM dynamic constraint and external force disturbance compensation is developed, and stable foot falling of the humanoid robot after the ball picking action is achieved; based on the principle of multi-rigid-body dynamics, a zero moment point is solved in real time by solving a balance equation of centroid acceleration inertia moment and gravity moment, a reinforcement learning reward function is designed in combination with support domain boundary constraint, the stability of single-foot support of the humanoid robot in a challenging task is enhanced, and finally stable control over the specified challenging position is achieved. Compared with other methods, the method has the advantage that the challenge accuracy can reach 95% or above.

The invention relates to the technical field of robot control, in particular to a predictive control humanoid robot anti-falling method and system, and the method comprises the steps: obtaining a real-time motion state and an environment perception data set of a robot, and carrying out the inversion with a mass center and a joint angle as initial states, so as to obtain a zero moment point trajectory prediction sequence; coupling terrain gradient, height and friction distribution parameters to generate a pre-contact surface state parameter set; performing combined stability boundary evaluation on the track sequence and the parameter set to generate an anti-drop pre-adjustment instruction; extracting a trajectory deviation point and a prediction moment, reversely deriving a centroid adjustment vector and a trunk attitude compensation amount, generating a collaborative motion and attitude compensation sequence, and correcting an original gait trajectory; a servo motor is driven to execute an anti-falling action, and the foot sole joint angle is adjusted according to the gradient; the anti-falling efficiency of the humanoid robot can be improved.

The invention discloses a quadruped robot stair climbing stability control method based on environmental perception and gait planning, and relates to the technical field of robot control, a robot identifies environmental parameters through a depth camera, calculates a landing point range and selects an optimal landing point; motion planning is carried out by combining the environment parameters and the optimal landing point position, and a foot bottom swing track is generated; a zero moment point is calculated according to the plantar force borne by the robot, and a mass center movement track is generated through the zero moment point; the deflection angle of the robot is adjusted according to data fed back in real time to keep balance, and stable control over stair climbing of the four-legged carrying robot is achieved. According to the method, the mass center movement track of the robot is planned through the zero moment point position, the instability of accelerated movement of the robot during stair climbing can be effectively reduced, the angular momentum change rate of the robot is reduced, meanwhile, the method is easier to adapt to the influence of mass center position change caused by load weight change on movement planning, and the accuracy of movement planning is improved. And the climbing stability and safety of the robot are improved.

The utility model discloses a humanoid robot, the trunk subassembly, femur subassembly and shank bone subassembly of this humanoid robot are provided with multiple inertia measurement units, the footboard assembly includes first, second, third, fourth ground contact subassembly, and it is connected in series through the pivot assembly in proper order, the first ground contact subassembly is located the forward direction of the trunk subassembly, the fourth ground contact subassembly is located the rear direction of the trunk subassembly, the fourth ground contact subassembly is connected through a pivot assembly on the downside of the shank bone subassembly, the footboard assembly is installed with pivot assembly and pressure sensing unit, through the detection of multiple inertia measurement units and multiple pressure sensing components, the humanoid robot can carry out ZMP zero moment point gait control, MPC model predictive control analysis, to reach the purpose of robot autonomous detection, barycentre balance.

The application discloses a dynamic running motion online planning method for a humanoid robot, wherein during the mutual switching process of the double-foot supporting state and the single-foot supporting periodic running state in the starting running and ending running stages of the humanoid robot, a nonlinear planning optimization is used to obtain an expected ZMP (Zero Moment Point) trajectory in the state switching process, so as to realize the smooth transition of the center of mass trajectory in the state switching process; during the acceleration / speed reduction switching process in the periodic running motion, an iterative optimization is used to calculate a suitable foot landing point, so as to realize the accurate tracking of the expected speed. The application can not only accurately follow the expected speed, but also realize the online planning of the whole running motion, and significantly improve the dynamic motion capability of the humanoid robot.

The application discloses a double-arm transfer nursing robot lower limb device for multiple nursing tasks, which comprises a body up-down adjusting mechanism, a chassis separation driving mechanism and a separable chassis mechanism; the body up-down adjusting mechanism is used for adjusting the height of the robot; the separable chassis mechanism comprises a left chassis module and a right chassis module; under the action of the chassis separation driving mechanism, the left chassis module and the right chassis module can approach or move away from each other, so as to adjust the size of the chassis; when the robot does not perform a task, a standby posture is kept, that is, the height of the robot is the lowest, the left and right chassis modules are symmetrically distributed about the left-right plane of the robot, and the spacing between the left and right chassis modules is the smallest; when the robot needs to perform a nursing task, the robot is moved to the side of a nursing person in the standby posture, the nursing person is supported, held horizontally or carried on the back, the height and the size of the chassis are adjusted, so that the center of gravity of the robot is the lowest and the zero moment point falls into the contact area between the robot and the ground. The device solves the problems that the existing double-arm transfer nursing robot has insufficient center of gravity adjusting capacity and is prone to instability when performing different tasks.