Abstract: An apparatus includes a memory and a hardware processor. The hardware processor determines one or more of a weight of an item, a packaging type of the item, a packaging material of the item, a barcode of the item, a rigidity of the item, or a physical response of the item to being lifted and determines a visual appearance of the item and a shape or size of the item. The hardware processor also compares, using a machine learning model, the determined characteristics of the item to a manifest for the container. The manifest identifies a plurality of items in the container. The hardware processor determines, using the machine learning model, an identity of the item based on comparing the determined characteristics of the item to the manifest.

Abstract: A control method for a robot includes a first working step of executing first work on a first working object by operating a robot arm by force control based on a predetermined position command value, a first memory step of storing first position information of a trajectory in which a control point set for the robot arm passes at the first working step, and a second working step of updating a position command value for the robot arm based on the first position information stored at the first memory step, and executing second work on a second working object by operating the robot arm by the force control based on an updated value as the updated position command value.

Abstract: It is possible to effectively prevent lowering of work efficiency while stabilizing an operation of a robot or the like. A torque estimation system estimates friction torque of a rotation mechanism. The torque estimation system inclues angular velocity detecting means for detecting an angular velocity of the rotation mechanism, and limit value setting means for setting an upper limit value and a lower limit value according to the angular velocity of the rotation mechanism detected by the angular velocity detection means, the upper limit value and the lower limit value limiting an upper limit and a lower limit, respectively, of the friction torque of the estimated friction torque.

Abstract: Spatial regions potentially occupied by a robot (or other machinery) or portion thereof and a human operator during performance of all or a defined portion of a task or an application are computationally estimated. These “potential occupancy envelopes” (POEs) may be based on the states (e.g., the current and expected positions, velocities, accelerations, geometry and/or kinematics) of the robot and the human operator. Once the POEs of human operators in the workspace are established, they can be used to guide or revise motion planning for task execution.

Abstract: Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to an artificial neural network training method that does not require extensive training data or time expenditure. The few-shot training model disclosed herein includes attempting to pick up items and, in response to a failed pick up attempt, transferring and generalizing information to similar regions to improve probability of success in future attempts. In some implementations, the training method is used to robotic device for picking items from a bin and perturbing items in a bin. When no picking strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points. In some implementations, the device may include one or more Computer-vision systems.

Abstract: This application provides a method for determining an automatic parking strategy. The method includes: determining, a target parking action corresponding to a current parking stage performing the target parking action; obtaining feedback information, where the feedback information is used to indicate whether a result of performing the target parking action reaches a predetermined objective, and the predetermined objective is a predetermined position of the vehicle relative to a target parking spot, and/or the predetermined objective is a status of the vehicle in the parking process; and updating the automatic parking strategy based on the feedback information. In the foregoing method, the entire parking process is divided into several parking stages, and a control strategy is obtained by using a different method at each stage. This can increase a success rate of automatic parking in a complex parking scenario.

Abstract: To provide personalized data for display on a map, a server device obtains location data for a user and identifies locations that are familiar to the user based on the frequency and recency in which the user visits the locations. The server device then provides the familiar locations in search results/suggestions and annotates the familiar locations with a description of a relationship between the familiar location and the user. The server device also includes the familiar locations as landmarks for performing maneuvers in a set of navigation instructions. Furthermore, the server device provides a familiar location as a frame of reference on a map display when a user selects another location nearby the familiar location. Moreover, the server device includes a familiar location as an intermediate destination when the user request navigation directions to a final destination.

Abstract: The present teaching relates to method, system, medium, and implementations for robot path planning. Depth data of obstacles, acquired by depth sensors deployed in a 3D robot workspace and represented with respect to a sensor coordinate system, is transformed into depth data with respect to a robot coordinate system. The 3D robot workspace is discretized to generate 3D grid points representing a discretized 3D robot workspace. Based on the depth data with respect to the robot coordinate system, binarized values are assigned to at least some of 3D grid points to generate a binarized representation for the obstacles present in the 3D robot workspace. With respect to one or more sensing points associated with a part of a robot, it is determined whether the part is to collide with any obstacle. Based on the determining, a path is planned for the robot to move along while avoiding any obstacle.

Abstract: Techniques are disclosed to perform robotic handling of soft products in non-rigid packaging. In various embodiments, sensor data associated with a workspace is received. An action to be performed in the workspace using one or more robotic elements is determined, the action including moving an end effector of one of the robotic elements relatively quickly to a location in proximity to an item to be grasped; actuating a grasping mechanism of the end effector to grasp the item using an amount of force and structures associated with minimized risk of damage to one or both of the item and its packaging; and using sensor data generated subsequent to the item being grasped to ensure the item has been grasped securely. Control communications are sent to the robotic element via the communication interface to cause robotic element to perform the action.

Abstract: A processing device according to one aspect of the present invention includes a vibration detecting unit configured to detect a vibration of a vehicle, an orientation detecting unit configured to detect an orientation of the vehicle, a storing unit configured to store information indicating the orientation of the vehicle, a processing unit configured to set an orientation of a vehicle on a map of a navigation system based on the information indicating the orientation of the vehicle, and a power supply controlling unit configured to control power supplied to the orientation detecting unit and the storing unit based on a detection result of the vibration detecting unit and in response to an accessory power of the vehicle turned OFF.

Abstract: The present disclosure provides a robot posture control method as well as a robot and a computer readable storage medium using the same. The method includes: constructing a virtual model of the robot, wherein the virtual model comprises a momentum wheel inverted pendulum model of the robot and an angle between a sole surface of the robot and a horizontal plane; and performing a posture control based on outer-loop feedback control, inner loop compensation for the external disturbance rejection in position level, inner loop external disturbance rejection via null-space in velocity level, and inner loop external disturbance rejection in force/acceleration level on the robot. In this manner, a brand-new virtual model is provided, which can fully reflect the upper body posture, centroid, foot posture, and the like of the robot which are extremely critical elements for the balance and posture control of the robot.

Abstract: A computing system and method for object recognition is presented. The method includes the computing system obtaining an image for representing the one or more objects, and generating a target image portion associated with one of the one or more objects. The computing system determines whether to classify the target image portion as textured or textureless, and selects a template storage space from among a first and second template storage space, wherein the first template storage space is cleared more often relative to the second template storage space. The first template storage space is selected in response to a textureless classification, and the second template storage space is selected as the template storage space in response to a textured classification. The computing system performs object recognition based on the target image portion and the selected template storage space.

Abstract: A control method includes: (a) setting a first operation mode using a first deviation threshold as a threshold to detect a deviation error in an amount of control and a second operation mode using a second deviation threshold that is higher than the first deviation threshold; and (b) selecting one of the first operation mode and the second operation mode and executing an operation of a robot.

Abstract: Methods, systems, and apparatus, for an autonomous vehicle navigation maintenance system. In one aspect, an autonomous vehicle monitoring system includes a mounting surface located on an autonomous vehicle, and a thermal imaging system affixed to the mounting surface, the thermal imaging system including a thermal imaging camera, a replaceable filter, and a filter fixture configured to affix the replaceable filter to the thermal imaging camera and aligned with an optical axis of the thermal imaging camera, and where maintenance of the replaceable filter does not include re-calibrating the thermal imaging camera.

Abstract: A method includes receiving an indication that a web-based application has been accessed for control of a robotic device by a mobile device, wherein the mobile device comprises one or more sensors to detect movement of the mobile device. The method further includes subscribing the web-based application to at least one motion event web API, wherein the at least one motion event web API listens normalizes motion data from the one or more sensors of the mobile device into one or more standardized motion parameters. The method additionally includes receiving the one or more standardized motion parameters of the mobile device from the at least one motion event web API. The method further includes converting the one or more standardized motion parameters into one or more requested movement commands for the robotic device. The method further includes sending the one or more requested movement commands to the robotic device.

Abstract: A method and system for hand tracking in a robotic system includes a hand tracking system and a controller coupled to the hand tracking system. The controller is configured to receive, from the hand tracking system, a plurality of locations of a hand; determine if the hand is in a first hand pose based on the plurality of locations; in response to determining that the hand is in the first hand pose, and switch the robotic system to a hand trajectory detection mode. While in the hand trajectory detection mode, the control unit is configured to detect, based on hand tracking information from the hand tracking system, that the hand has performed a first hand trajectory of a plurality of known hand trajectories; and in response to detecting the first hand trajectory, change a mode of operation of the robotic system.

Abstract: During machining of a workpiece, a gripping force adjustment device takes into account the state of the machining and the state of the workpiece in order to set a more appropriate gripping force. The gripping force adjustment device acquires data indicating a machining state implemented by a machine tool and data relating to a gripping state realized on the workpiece by a jig, and creates data to be used in machine learning on the basis of the acquired data. The gripping force adjustment device then executes machine learning processing relating to the gripping force exerted on the workpiece by the jig in the environment in which the machine tool machines the workpiece on the basis of the created data.

Abstract: Systems, methods, and non-transitory computer-readable media can receive stop point data from a plurality of sources. The stop point data can be aggregated into a central repository. A request for stop point data at a particular location can be received from a first vehicle. The stop point data at the particular location stored in the central repository can be transmitted to the first vehicle.

Abstract: An apparatus for calibration of a robotic arm having an end effector of a robot includes a magnetic coupler having a body, a receiving face, a mounting member, and a magnetic portion. The mounting member is configured to fixedly connect to the end effector of the robotic arm. A mechanical digitizer probe having a ball and a handle are provided, where the ball is fixedly attached to a distal end of the handle and the ball is removably coupled to the magnetic coupler via the magnetic portion on the receiving face to form a rotatable ball and socket connection, and where a proximal end of the handle is adapted to be attached to a mechanical digitizer associated with the robot. A method for calibration of the robotic arm of a robot is also detailed.

Abstract: A detection system and detection method for the sensors of a robot. A detection system installs three sensors at the motor side and power output terminal of the robot. A detection unit detects the normal or abnormal state of three sensors to index the abnormal sensor for maintenance, and two normal sensors are selected for keeping the robot safety operation without stop.