Abstract: An inertia braking test system and a control method is provided, wherein the inertia braking test system is composed of an inertia brake test system, a sensor system and a tested object. An actuating device is connected with the inertia brake control device through a ball stud. The actuation function of the inertia brake control device with two degrees of freedom along the front-and-rear direction and the up-and-down direction of the vehicle is realized. The movable chassis realizes the mobile function of the system. The acceleration sensor can sense the acceleration of the movable chassis. Each force is tested by the first force sensor, the second force sensor and the third force sensor. The displacement data is measured by the first displacement sensor and the second displacement sensor, so that a movable brake system test is achieved.

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: The present disclosure relates to a positioning method, a positioning server, and a positioning system. The positioning method includes: receiving a wireless positioning coordinate of a moving object; determining a visual sub-map to be matched in a visual map database based on the wireless positioning coordinate; and obtaining a visual positioning coordinates corresponding to a current image of the moving object captured at time of wireless positioning as a positioning result, based on the determined visual sub-map to be matched.

Abstract: An inertia braking test system and a control method is provided, wherein the inertia braking test system is composed of an inertia brake test system, a sensor system and a tested object. An actuating device is connected with the inertia brake control device through a ball stud. The actuation function of the inertia brake control device with two degrees of freedom along the front-and-rear direction and the up-and-down direction of the vehicle is realized. The movable chassis realizes the mobile function of the system. The acceleration sensor can sense the acceleration of the movable chassis. Each force is tested by the first force sensor, the second force sensor and the third force sensor. The displacement data is measured by the first displacement sensor and the second displacement sensor, so that a movable brake system test is achieved.

Abstract: Systems and methods are described for provisioning a desktop interface at a cloud service provider. An application service is introduced that selects a cloud service provider for provisioning a virtual machine (“VM”) that hosts the desktop interface. In an example, a user can request access to a virtual desktop from a client device. The application service can retrieve network latency data from multiple cloud service providers and select the provider with the lowest network latency for the client device. In some examples, the application service can select the cloud service provider on additional factors, such as the cost of provisioning the VM at each cloud service provider. The application service can provision the VM at the selected cloud service provider and facilitate access to the virtual desktop for the client device.

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.

Abstract: Embodiments of the present disclosure relate to techniques for providing a remoted application to a client device over a network. Certain embodiments involve receiving, by a web server and from the client device, a request for the remoted application. The request may comprise a tag which identifies one or more attributes of the remoted application. Embodiments further involve launching, by the web server and based on the tag, the remoted application. Embodiments further involve providing, by the web server and to the client device, a video stream of the remoted application. The video stream of the remoted application may comprise one or more images rendered based on raw data of the remoted application. Embodiments further involve receiving, by the web server and from the client device, user input and providing, by the web server and based on the user input, application input to the remoted application.

Abstract: Systems and methods are provided for dynamic GPU-enabled VM provisioning across cloud service providers. An example method can include providing a VM pool that includes a GPU-optimized VM and a non-GPU-optimized VM operating in different clouds. A control plane can receive an indication that a user has submitted a machine-learning workload request, determine whether a GPU-optimized VM is available and instruct the non-GPU-optimized VM to send the workload to the GPU-optimized VM in a peer-to-peer manner. The GPU-optimized VM computes the workload and returns a result to the requesting VM. The control plane can instantiate a new GPU-optimized VM (or terminate it when the workload is complete) to dynamically maintain a desired number of available GPU-optimized VMs.

Abstract: A robot climbing control method is disclosed. A gravity direction vector in a gravity direction in a camera coordinate system of a robot is obtained. A stair edge of stairs in a scene image is obtained and an edge direction vector of the stair edge in the camera coordinate system is determined. A position parameter of the robot relative to the stairs is determined according to the gravity direction vector and the edge direction vector. Poses of the robot are adjusted according to the position parameter to control the robot to climb the stairs.

Abstract: A robot climbing control method is disclosed. The method obtains an RGB color image and a depth image of stairs, extracts an outline of a target object of a target step on the stairs from the RGB color image, determines relative position information of the robot and the target step according to the depth image and the outline of the target object, and controls the robot to climb the target step according to the relative position information. The embodiment of the present disclosure allows the robot to effectively adjust postures and forward directions on any size of and non-standardized stairs and avoids the deviation of the walking direction, thereby improving the effectiveness and safety of the stair climbing of the robot.

Abstract: A method includes: performing target detection on a current image to obtain detection information of a plurality of detected targets; obtaining position prediction information of each of a plurality of tracked targets and a number of times of tracking losses of targets from tracking information of each of the tracked targets, and determining a first matching threshold for each of the tracked targets according to the number of times of tracking losses of targets; calculating a motion matching degree between each of the tracked targets and each of the detected targets according to the position detection information and the position prediction information; for each of the tracked targets, obtaining a motion matching result according to the motion matching degree and the first matching threshold corresponding to the tracked target; and matching the detected targets and the tracked targets according to the motion matching results to obtain a tracking result.

Abstract: The present disclosure provides a gesture recognition method as well as a terminal device and a computer-readable storage medium using the same. The method includes: obtaining a video stream collected by an image recording device in real time; performing a hand recognition on the video stream to determine static gesture information of a recognized hand in each video frame of the video stream; encoding the static gesture information in the video frames of the video stream in sequence to obtain an encoded information sequence of the recognized hands; and performing a slide detection on the encoded information sequence using a preset sliding window to determine a dynamic gesture category of each recognized hand. In this manner, static gesture recognition and dynamic gesture recognition are effectively integrated in the same process. The dynamic gesture recognition is realized through the slide detection of the sliding window without complex network calculations.

Abstract: A method of establishing a secure communication channel from a first edge device that is in a first network zone across a secure overlay network to a second edge device that is in a second network zone, so that access to a computing device that is in the second network zone can be authenticated by an authentication service that is in the first network zone, includes the steps of establishing a first secure communication channel from the first edge device to the secure overlay network, receiving a request to join the secure overlay network along with administrator credential information and, responsive to the request, transmitting the administrator credential information to the authentication service for authentication through the first secure communication channel and the first edge device, and establishing a second secure communication channel from the second edge device to the secure overlay network if the authentication is received from the authentication service.

Abstract: The present disclosure relates to robot technology, which provides a robot pose estimation method as well as an apparatus and a robot using the same. The method includes: obtaining, through an inertial measurement unit, initial 6DoF pose data; performing a first correction on the initial 6DoF pose data based on pose data obtained through an auxiliary sensor to obtain corrected 6DoF pose data; obtaining, through a 2D lidar sensor disposed on a stable platform, 3DoF pose data; and performing a second correction on the corrected 6DoF pose data based on the 3DoF pose data to obtain target 6DoF pose data. In this manner, the accuracy of the pose data of the robot is improved, and the accurate pose estimation of the robot is realized.

Abstract: A millimeter wave radar gesture recognition method and device based on trajectory judgment are provided. The method includes steps as follows: Step 1, obtaining data information of each point of a hand trajectory according to echo signals. Step 2, setting a retrieval method of trajectory start point and end point, do not miss any gestures while reducing repeated trajectory judgments. Step 3, for a trajectory with given start point and end point, calculating slopes of least squares straight lines of Y coordinates and Z coordinates with respect to t coordinates which represent time respectively, then precluding impossible basic gestures and judging whether current gesture is one of remaining basic gestures. Step 4, if continuously determined basic gestures constitute a combined gesture, outputting the combined gesture determination result.

Abstract: The present disclosure provides a gesture recognition method as well as a terminal device and a computer-readable storage medium using the same. The method includes: obtaining a video stream collected by an image recording device in real time; performing a hand recognition on the video stream to determine static gesture information of a recognized hand in each video frame of the video stream; encoding the static gesture information in the video frames of the video stream in sequence to obtain an encoded information sequence of the recognized hands; and performing a slide detection on the encoded information sequence using a preset sliding window to determine a dynamic gesture category of each recognized hand. In this manner, static gesture recognition and dynamic gesture recognition are effectively integrated in the same process. The dynamic gesture recognition is realized through the slide detection of the sliding window without complex network calculations.

Abstract: A method of establishing a secure communication channel from a first edge device that is in a first network zone across a secure overlay network to a second edge device that is in a second network zone, so that access to a computing device that is in the second network zone can be authenticated by an authentication service that is in the first network zone, includes the steps of establishing a first secure communication channel from the first edge device to the secure overlay network, receiving a request to join the secure overlay network along with administrator credential information and, responsive to the request, transmitting the administrator credential information to the authentication service for authentication through the first secure communication channel and the first edge device, and establishing a second secure communication channel from the second edge device to the secure overlay network if the authentication is received from the authentication service.

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: A robot climbing control method is disclosed. A gravity direction vector in a gravity direction in a camera coordinate system of a robot is obtained. A stair edge of stairs in a scene image is obtained and an edge direction vector of the stair edge in the camera coordinate system is determined. A position parameter of the robot relative to the stairs is determined according to the gravity direction vector and the edge direction vector. Poses of the robot are adjusted according to the position parameter to control the robot to climb the stairs.

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.