Abstract: A vision-based tactile measurement method is provided, performed by a computer device (e.g., a chip) connected to a tactile sensor, the tactile sensor including a sensing face and an image sensing component, and the sensing face being provided with a marking pattern. The method includes: obtaining an image sequence collected by the image sensing component of the sensing face, each image of the image sequence comprising one instance of the marking pattern; calculating a difference feature of the marking patterns in adjacent images of the image sequence; and processing the difference feature of the marking patterns using a feedforward neural network to obtain a tactile measurement result, a quantity of hidden layers in the feedforward neural network being less than a threshold.

Abstract: This disclosure relates to a spatial calibration method and apparatus of a robot ontology coordinate system based on a visual perception device and a storage medium. The method includes: obtaining first transformation relationships; obtaining second transformation relationships; using a transformation relationship between a visual perception coordinate system and an ontology coordinate system as an unknown variable; and resolving the unknown variable based on an equivalence relationship between a transformation relationship obtained according to the first transformation relationships and the unknown variable and a transformation relationship obtained according to the second transformation relationships and the unknown variable, to obtain the transformation relationship between the visual perception coordinate system and the ontology coordinate system.

Abstract: Provided herein are prime editing methods and compositions for treatment of genetic disorders such as amyotrophic lateral sclerosis.

Abstract: Embodiments of the present disclosure provide a slip simulation apparatus, a controlled robot, a game handle, a virtual game console, and a control system. The slip simulation apparatus includes a base; at least one motor arranged on the base; a slip simulation controller, configured to: receive slip data, and generate a rotating speed control signal used for controlling the at least one motor; and at least one synchronous wheel, at least one synchronous belt, and at least one limit apparatus associated with the motor, the synchronous wheel being sleeved on the synchronous belt and the limit apparatus, the motor being drivingly connected to the at least one synchronous wheel to drive, according to the rotating speed control signal, the at least one synchronous wheel and the at least one synchronous belt to rotate.

Abstract: An information handling system stores a list of commands associated with test cases. The system receives the list of commands associated with the test cases, and provides the list of commands to an input layer of a state attributes probability machine learning model. An output layer of the of the state attributes probability machine learning model outputs a state attributes probability. The state attributes probability identifies an overlap of state attributes of test steps in the test cases. Based on the state attributes probability, the system determines whether the test steps of the test cases are in conflict. In response to the test steps not being in conflict, the system merges the test cases. In response to the test steps being in conflict, the system stops a merging of the test cases.

Abstract: The present invention discloses a method for identifying collision regions of boundary layer convergence lines prone to trigger local convection, including the following steps: S1: collecting and pre-processing data; S2: manually labeling and screening an image data set, and designing a multi-scale anchor box according to a label set by using a clustering analysis method; S3: constructing an R2CNN deep learning module, setting reasonable anchor window parameters, and training the model; S4: detecting an image by using the trained model to obtain detection results of rotating bounding boxes, and scoring the detection results; correcting and fusing the detection results of the overlapped bounding boxes to obtain an identification result of the plurality of boundary layer convergence lines; and S5: positioning and identifying regions prone to trigger the local convection.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a pull-over location using machine learning. One of the methods includes obtaining data specifying a target pull-over location for an autonomous vehicle travelling on a roadway. A plurality of candidate pull-over locations in a vicinity of the target pull-over location are identified. For each candidate pull-over location, an input that includes features of the candidate pull-over location is processed using a machine learning model to generate a respective likelihood score representing a predicted likelihood that the candidate pull-over location is an optimal location. The features of the candidate pull-over location include one or more features that compare the candidate pull-over location to the target pull-over location. Using the respective likelihood scores, one of the candidate pull-over locations is selected as an actual pull-over location for the autonomous vehicle.

Abstract: Provided herein are prime editing methods and compositions for treatment of genetic disorders such as myotonic dystrophy.

Abstract: A legged robot motion control method, apparatus, and device, and a storage medium. The method includes: acquiring center of mass state data corresponding to a spatial path starting point and spatial path ending point of a motion path; determining a candidate foothold of each foot in the motion path based on the spatial path starting point and the spatial path ending point; determining a variation relationship between a center of mass position variation coefficient and a foot contact force based on the center of mass state data; screening out, under restrictions of a constraint set, a target center of mass position variation coefficient and target foothold that satisfy the variation relationship; determining a target motion control parameter according to the target center of mass position variation coefficient and the target foothold; and controlling a legged robot based on the target motion control parameter to move according to the motion path.

Abstract: A method and an apparatus for driving a display panel, and a display driver integrated circuit chip are provided. The method includes: determining an order in which display divisions on the display panel are to be driven, when determined not to update respective refresh rates of the display divisions; determining electric signal gear ranges for the display divisions based on the refresh rates of the display divisions, respectively; and driving the display divisions sequentially in the determined order and based on the determined gear ranges. With this method, the power consumption can be reduced while the display effect is improved.

Abstract: A two-sided time-sharing driving and acquisition system based on dry contacts comprises k dry contacts, a processor, p acquisition circuits, and m driving circuits. The p acquisition circuits are evenly divided into two groups which are separately disposed at two sides of the k dry contacts. The m driving circuits are separately disposed at the two sides of the k dry contacts. A system fault detection method and the two-sided time-sharing driving and acquisition system have the following advantages: the state of input acquisition circuits and cables monitored in real time during system debugging or running, and faults caused by exceptions of the acquisition circuits and the cables can be reported in time.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a pull-over location using machine learning. One of the methods includes obtaining data specifying a target pull-over location for an autonomous vehicle travelling on a roadway. A plurality of candidate pull-over locations in a vicinity of the target pull-over location are identified. For each candidate pull-over location, an input that includes features of the candidate pull-over location is processed using a machine learning model to generate a respective likelihood score representing a predicted likelihood that the candidate pull-over location is an optimal location. The features of the candidate pull-over location include one or more features that compare the candidate pull-over location to the target pull-over location. Using the respective likelihood scores, one of the candidate pull-over locations is selected as an actual pull-over location for the autonomous vehicle.

Abstract: Embodiments of this application relate to the field of communication technologies, and provide a routing information publishing method. The method includes: An edge transport device connected to a first edge device in a first network domain receives, based on a control plane protocol message, first routing information that is from a controller and that includes an address of a second edge device in a second network domain and a destination address of the second network domain, and sends the first routing information to the first edge device, so that the first edge device generates, based on the first routing information, a forwarding table that is of the first edge device and that is used to indicate a forwarding relationship between the first network domain and the second network domain.

Abstract: This application provide a method for controlling the landing of a legged robot on a plane. The legged robot includes a base and at least two robotic legs, each leg including at least one joint. The method includes: determining a first expected moving trajectory and a second expected moving trajectory corresponding to the legged robot in response to determining that the legged robot is going to contact a plane, the first expected moving trajectory indicating an expected moving trajectory of a center of mass of the legged robot and an expected moving trajectory of a change in a tilt angle of the legged robot, and the second expected moving trajectory indicating an expected moving trajectory of a foot end of each robotic leg; and controlling, based on a dynamic model and the first and second moving trajectories, an action of each joint after the legged robot contacts the plane.

Abstract: A swing-up motion method of a robot includes: receiving a swing-up motion instruction; controlling, in response to the swing-up motion instruction, first leg parts of a robot to be in a suspended state, performing a leg retraction movement of the first leg parts, and at the end of the suspended state, placing first mechanical wheels on knee joints of the first leg parts on the ground; and controlling second leg parts of the robot to be suspended and keeping stable in a balanced state by using the first mechanical wheels as force-bearing balance points.

Abstract: A method including obtaining an optimization request at a coordinating engine. The method also can include triggering engines to process the optimization request. At least one of the engines divides the optimization request into subproblems. At least a portion of the engines solve the subproblems. Respective instances of at least one of the engines are triggered to handle respective ones of the subproblems. Each of the engines provides a dynamic algorithmic flow using modularized algorithmic solvers. The dynamic algorithmic flow is adjusted based on a respective input to each of the engines. The method additionally can include outputting, from the coordinating engine, one or more results in response to the optimization request, based on results for the subproblems generated by the engines. Other embodiments are described.

Abstract: Aspects of the disclosure include a method and an apparatus. The method includes generating second relational data indicating a relationship between a movement duration and force(s) applied to a legged robot and third relational data indicating a relationship between the force(s) and a predicted rotational angle of the legged robot. The second relational data includes a vector C to be determined. Fourth relational data is generated based on the third relational data. The fourth relational data indicates a positive correlation between a target value J associated with C and a status data error between predicted status data and target status data. C that minimizes J is determined based on the second relational data and the fourth relational data. First relational data with the determined C representing a movement trajectory of a torso of the legged robot is determined. The legged robot is caused to move based on the movement trajectory.

Abstract: The present disclosure discloses a motion control method and apparatus for a legged robot, a legged robot, a computer-readable storage medium, and a computer program product. The legged robot includes at least two foot-ends. The method includes: receiving a bound instruction for the legged robot in response to the foot-ends of the legged robot standing in unit regions that are independent from one another, the bound instruction being used for instructing the legged robot to bound to a target unit region from at least two unit regions in which the legged robot is currently located; and controlling the legged robot to bound to the target unit region in response to the bound instruction, a distance between any two foot-ends of the legged robot in the target unit region being less than a distance between two corresponding foot-ends before bounding.