Ubtech Robotics Corp Ltd

Ubtech North America Research and Development Center Corp

Ubkang (Qingdao) Technology Co., Ltd.

Ubertech Robotics Corp.

Ubtech Education (Shenzhen) Co., Ltd

2021a351us1

Youjun Xiong

Jianxin Pang

Yizhang Liu

Ligang Ge

Chunyu Chen

Wenhua Fan

Hongyu Ding

Zheng Xie

Mingguo Zhao

Zhichao Liu

Lifu Zhang

Youpeng Li

Wenhua Yu

Gaobo Huang

Jie Bai

Wenquan Shu

Jiawen Hu

Musen Zhang

Qi Zhao

Xinpu Chen

Kunlei Zhao

Yuesong Wang

Libing Zhou

Yongsheng Zhao

Huan Tan

Dong Liu

Chengkun Zhang

Jiangchen Zhou

Xiangbin Huang

Meichun Liu

Hailang Zhou

Jun Cheng

Lefeng Liu

Hongge Wang

Xi Bai

Hanyu Sun

Zhongliang Wang

Qiuyue Luo

Dongyan Huang

Xiaoyu Ren

Liqun Huang

Chenchen Jiang

Jian Zhang

Miaochen Guo

Zhihao Zhang

Defu Liu

Shuping Hu

Peng Nie

Zhanjia Bi

Malin Wang

Jingtao Zhang

Zuyi Mao

Lin Chen

Dong Wang

Rui Guo

Xinshui Huang

Yong Fu

Xuchao Du

Gao Yang

Wei He

Yumiao Wu

Xiongyuan Fang

Feng Hu

Sheng Zhou

Yusheng Zeng

Yang Liu

Jiebin Xie

Yu Tang

Francisco Jose Hernandez

Xuan Luo

Brandon Jon LaPlante

Shixun Chen

Li Ma

Jing Shi

Yu Zhang

Jian Wang

Dingkai Xing

Hao Dong

Jinliang Chen

Jianbo Li

Yiping Li

Rui Gu

Shuo Zhang

Jian Tong Li

Yang Wang

Jing Yang

Jing Gu

Yan Zhou

Xiang Liu

Yun Zhao

Yue Wang

Wei Fang

Xue Yang

Tao Bai

Xian Li

Jian Zhou

Zhihua Zhang

Bin He

Kang Li

Tao Xu

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.

Arm angle interval solving method and robotic arm using the same

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.

Robot calibration method, robot and computer-readable storage medium

A method for detecting contact of a swinging leg of a robot with ground includes: obtaining a torque on each joint of the swinging leg when the robot is in a swing phase; estimating a force on a foot of the swinging leg by using a force Jacobian matrix based on the torque on each joint of the swinging leg, and calculating a rate of change of force of the foot in a vertical direction according to the force on the foot; and determining that the swinging leg has contacted the ground in response to a preset consecutive number of values of the rate of change of force being greater than a preset threshold.

Method for foot/ground contact detection for robot, robot and computer-readable medium

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.

Humanoid robot balance control method, humanoid robot, and storage medium

A multi-legged robot load balancing method, a multi-legged robot, and a storage medium are provided. The method includes: calculating a current position and velocity of a load positioned on a torso according to a value measured by a force sensor; calculating, through a feedback control law, a desired posture of the torso required for keeping a balance of the load according to the current position and the current velocity of the load; determining an expected position of virtual joints according to the desired posture of the torso, and calculating, using a full dynamics control algorithm of the robot, a joint torque for each real joint of the robot according to the expected position; and transmitting the calculated joint torques to the corresponding real joints so that the torso is moved to reach the desired posture by moving the corresponding real joints.

Multi-legged robot load balancing method, multi-legged robot, and storage medium

A path generation method for a robot includes: based on a scene model of a current scene and a machine model corresponding to the robot, combined with multiple configurations of the robot, determining a plurality of initial points between a start point and an end point in the scene model; removing redundant points from the plurality of the initial points to obtain necessary points among the initial points; and connecting the necessary points to obtain a path between the start point and the end point.

Path generation method for robot, robot and computer-readable storage medium

A method for controlling a robot includes: obtaining current motion state information of the robot and desired motion trajectory information corresponding to a target task; determining task execution coefficient matrices corresponding to the robot performing the target task according to the desired motion trajectory information and the motion state information; constructing matching dynamic constraints for task-driven parameters of the robot according to the desired motion trajectory information and the motion state information; constructing matching parameter distribution constraints for the task-driven parameters according to the motion state information and body action safety constraints corresponding to the target task; solving a pre-stored task execution loss function by using the task execution coefficient matrices to obtain the target-driven parameters satisfying the dynamic constraints and the parameter distribution constraints; and controlling operation state of each joint end effector of the robot according to the target-driven parameters.

Method for controlling robot, robot and computer-readable storage medium

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.

Admittance control method, robot, and computer-readable storage medium

A dynamic target tracking method for a robot having multiple joints includes: obtaining a motion state of a tracked dynamic target in real time; performing motion prediction according to the motion state at a current moment to obtain a predicted position of the dynamic target; performing lag compensation on the predicted position to obtain a compensated predicted position; performing on-line trajectory planning according to the compensated predicted position to obtain planning quantities of multi-step joint motion states at multiple future moments, and determining a multi-step optimization trajectory according to the planning quantities and a multi-step optimization objective function; and controlling the joints of the robot to according to the multi-step optimization trajectory.

Dynamic target tracking method, robot and computer-readable storage medium

A footstep planning method includes: obtaining a number of depth images of an environment in a walking direction of a legged robot; creating a three-dimensional model of the environment based on the depth images; determining at least one even region from the three-dimensional model of the environment; and selecting one or more of the at least one even region as one or more candidate footstep locations for the legged robot to step on.

Footstep planning method, robot and computer-readable storage medium

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.

Motion terrain determining method, robot, and computer-readable storage medium

A navigation method for a disinfection robot includes: obtaining an initial map within a field of view of the robot; generating a disinfection grid having multiple disinfection squares on the initial map, and determining multiple disinfecting consideration points in the disinfection squares; determining a disinfection order of disinfecting targets corresponding to the disinfection squares according to distances between the robot after the robot completes disinfection of one of the targets corresponding to one of the disinfection squares and to-be-disinfected ones of the disinfection squares; according to distances between the position and the disinfecting consideration points in to-be-disinfected ones of the disinfection squares, combined with priority levels of the disinfecting consideration points in to-be-disinfected ones of the disinfection squares, determining disinfecting planning points in the disinfection squares; and performing disinfection to the targets corresponding to the disinfection squares according to the disinfection order and the disinfecting planning points.

Navigation method for disinfection robot, robot and computer-readable storage medium

A robot state estimation method, a computer-readable storage medium, and a legged robot are provided. The method includes: obtaining force information of a left leg of a robot and a right leg of the robot; calculating a ZMP of the robot in a world coordinate system based on the force information of the left leg and the force information of the right leg; and calculating a position of a center of mass (CoM) of the robot based on a preset linear inverted pendulum model. In this manner, a brand-new linear inverted pendulum model is constructed in advance, which uses the ZMP of the robot as a supporting point of the model, thereby fully considering the influence of the change of the position of the ZMP of the robot on the position of the CoM.

Robot state estimation method, computer-readable storage medium, and legged robot

A method for navigating a robot through a limited space includes: obtaining a planned first path for the robot to reach a target position; calculating curvature and/or normal vectors of points in the first path; according to the curvature and a preset curvature threshold, and/or according to the normal vectors and a preset normal vector change threshold, obtaining a first straight path for the robot outside the limited space by curve fitting; determining an intersection of a centerline of the limited space and the first straight path, and determining a second straight path for the robot to move through the limited space according to the centerline and the intersection; and generating a second path for the robot to move through the limited space based on the first straight path and the second straight path, and navigating the robot to move through the limited space according to the second path.

Method for navigating root through limited space, robot and computer-readable storage medium

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.

Walking control method, biped robot and computer-readable storage medium

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Shenzhen, China

Youjun Xiong