Abstract: Embodiments of present disclosure relates to an apparatus and a method for calibrating a laser displacement sensor for use with a robot. The apparatus comprises an auxiliary object arranged in a work space of the robot or held by the robot and comprising a planar surface adapted to be detected by the laser displacement sensor; and a controller configured to: determine a characteristic point on the planar surface of the auxiliary object based on a detection result from the laser displacement sensor; cause the laser displacement sensor to point at the characteristic point for plural times with the same angle and different distances to obtain an orientation of the laser displacement sensor; and cause the laser displacement sensor to point at the characteristic point for plural times with different angles and the same distance to obtain a relative position relationship between the laser displacement sensor and the robot.

Abstract: The transportation vehicle determines whether the calculated distance is equal to or less than the predetermined distance (step S14). If the determination result of step S14 is positive, the transportation vehicle searches for the closest stoppable location to the current location (step S15). The transportation vehicle also performs the pause task at the closest stoppable location. The transportation vehicle performs visualization processing of the surrounding circumstances of the drop-off location, and displays the processed image on touch-screen. The user specifies the detailed drop-off location while looking at the touch-screen (step S16).

Abstract: Examples provide a system for system for customized item decanting. A robotic picker device is configured to remove a selected item from a selected case in an open configuration on a conveyor device. A decan manager, implemented on a processor, is configured to identify a destination tote in a set of totes for placement of the selected item, The robotic picker device places the selected item into the destination tote and the decant manager analyzes sensor data and item data associated with the selected item to confirm an identification of the selected item placed into the destination tote for inventory update.

Abstract: A method for teaching a robot to perform an operation based on human demonstration with images from a camera. The method includes a teaching phase where a 2D or 3D camera detects a human hand grasping and moving a workpiece, and images of the hand and workpiece are analyzed to determine a robot gripper pose and positions which equate to the pose and positions of the hand and corresponding pose and positions of the workpiece. Robot programming commands are then generated from the computed gripper pose and position relative to the workpiece pose and position. In a replay phase, the camera identifies workpiece pose and position, and the programming commands cause the robot to move the gripper to pick, move and place the workpiece as demonstrated. A teleoperation mode is also disclosed, where camera images of a human hand are used to control movement of the robot in real time.

Abstract: The delivery management system stores identification information identifying an article to be delivered to a user and storage place information indicating a storage place of the article in a living space of the user while associating the identification information and the storage place information with each other, and reads the identification information attached to the article and extracts the storage place information associated with the identification information when the article arrives at a delivery destination.

Abstract: A measurement parameter for use when measuring an object with a measuring device provided on a robot may be adjusted and optimized significantly more easily than in conventional technology. A measurement parameter optimization method or operations performed by a processor may include: acquiring N captured images of objects with first measurement parameters; estimating recognized object counts Zi for the objects based on acquiring N/j captured images of the objects with second measurement parameters, and storing the recognized object counts Zi as first data; based on acquiring N/j/k captured images of the objects with third measurement parameters, estimating recognized object counts Zi for the objects based on the first data and storing the recognized object counts Zi as second data; and determining an optimized measurement parameter that satisfies a predetermined judgment criterion from among the second data.

Abstract: A vehicle control device includes a tracking unit estimating a motion of a moving object, a model selection unit selecting a motion model corresponding to a moving object type, an abnormality determination unit determining a presence or absence of an abnormality of the estimation of the motion of the moving object based on the estimated moving object motion and the motion indicated by the motion model, and a control unit. A control mode in which the control unit controls traveling of a host vehicle when the abnormality determination unit determines that the abnormality is present differs from a control mode in which the control unit controls the traveling of the host vehicle when the abnormality determination unit determines that the abnormality is absent.

Abstract: A device and method for controlling a robotic device. The method includes: training a control model, which includes a parameter model and an object model, including: providing for each initial state-target state pair of a plurality of initial state-target state pairs a control state sequence, including states and transition states, each transition state being assigned a set of task parameters; ascertaining a set of state transition-state-state transition triples, and for each: adapting the parameter model so that the parameter model ascertains a probability distribution for each task parameter from the set of task parameters, which is assigned to the state transition following the state, adapting the object model so that the object model ascertains for each object a probability distribution for the state of the object; and controlling the robotic device with the control model using the trained parameter model and the trained object model.

Abstract: A vehicle and a system method of operating the vehicle is disclosed. The system includes a monitoring module and a mitigation module operating on a processor. The monitoring module is configured to measure a degradation in an operation parameter of the vehicle, the vehicle operating in a first state based on a first value of a set of adaptive parameters. The mitigation module is configured to determine a threat to the vehicle due to operating the vehicle in the first state with the degradation in the operation parameter and adjust the set of adaptive parameters from the first value to a second value that mitigates the threat to the vehicle, wherein the processor operates the vehicle in a second state based on the second value.

Abstract: A bicycle electric component setting system is basically provided a master unit and a plurality of slave bicycle electric components. The master unit is configured to be mounted to a bicycle. The master unit is configured to receive update information from an external terminal device. The slave bicycle electric components are configured to be mounted to the bicycle. The slave bicycle electric components are configured to receive the update information from the master unit to change a setting of at least one of the slave bicycle electric components.

Abstract: A controller is provided for interactive classification and recognition of an object in a scene using tactile feedback. The controller includes an interface configured to transmit and receive the control, sensor signals from a robot arm, gripper signals from a gripper attached to the robot arm, tactile signals from sensors attached to the gripper and at least one vision sensor, a memory module to store robot control programs, and a classifier and recognition model, and a processor to generate control signals based on the control program and a grasp pose on the object, configured to control the robot arm to grasp the object with the gripper.

Abstract: Systems and methods for virtual vehicle parking assistance are disclosed herein. An example method includes determining a current vehicle position and vehicle dimensions of a vehicle, determining parking space dimensions of a parking space, receiving a desired parking position for the vehicle through an augmented reality interface, the augmented reality interface including a three-dimensional vehicle model based on the vehicle dimensions, the augmented reality interface being configured to allow a user to virtually place the three-dimensional vehicle model in the parking space to determine the desired parking position, determining a virtual parking procedure for the vehicle based on the desired parking position selected by the user and the parking space dimensions of a parking space and causing the vehicle to autonomously park based on the virtual parking procedure.

Abstract: A robotic system comprising a master robotic system, and a first robotic system comprising a first mobile platform operable to move about a surface, and comprising a first manipulator. The robotic system can comprise a second robotic system comprising a second mobile platform operable to move about the surface, and comprising a second manipulator. A control module can be associated with the master robotic system and the first and second robotic systems, and can be operable in a paired control mode to facilitate paired control of the first and second robotic systems to move about the ground surface, and operable in an unpaired control mode to facilitate non-paired control of a selected one of the first or second robotic systems.

Abstract: While operating a vehicle on a travel path, a width of the travel path is determined based on a map. Upon detecting a presence or an absence of a target vehicle in the travel path, a lateral position for the vehicle on the travel path is determined based on the width of the travel path and the presence or absence of the target vehicle. The vehicle is controlled to operate according to the determined lateral position on the travel path and a speed of the vehicle that is based on the determined lateral position on the travel path.

Abstract: Collision avoidance for a mobile machine having a plurality of sensors is disclosed. The mobile machine is avoided from colliding with a collision object by fusing sensor data received from the plurality of sensors to obtain a plurality of data points corresponding to the collision object, calculating a closed-form solution of a distance between the mobile machine and each of the plurality of data points, calculating a maximum allowed velocity of the mobile machine based on the shortest distance between the mobile machine and the plurality of data points and a current velocity of the mobile machine, and controlling the mobile machine to move according to the maximum allowed velocity.

Abstract: In a robot utilization system using a plurality of transport robots, the transport robot includes a traveling mechanism having a traveling function, a main body supported by the traveling mechanism and configured to receive products, and a specifying unit configured to specify the products received by the main body. The transport robots include a transport robot that performs a purchase process of the products received by the main body, and a transport robot that performs a return process of the products received by the main body.

Abstract: A method for prioritizing occlusion information is presented. The method includes determining, at a first time period, a first sensor's view of a spatial area is occluded. The method also includes observing, at a second time period, the spatial area. The method further includes determining a level of risk associated with the spatial area based on the observation. The method still further includes prioritizing transmission of the occlusion information corresponding to the spatial area based on the determined level of risk and transmitting the occlusion information corresponding to the spatial area based on the priority.

Abstract: Described herein are systems and methods that improve the success rate of relocalization and eliminate the ambiguity of false relocalization by exploiting motions of the sensor system. In one or more embodiments, during a relocalization process, a snapshot is taken using one or more visual sensors and a single-shot relocalization in a visual map is implemented to establish candidate hypotheses. In one or more embodiments, the sensors move in the environment, with a movement trajectory tracked, to capture visual representations of the environment in one or more new poses. As the visual sensors move, the relocalization system tracks various estimated localization hypotheses and removes false ones until one winning hypothesis. Once the process is finished, the relocalization system outputs a localization result with respect to the visual map.

Abstract: A system and/or method comprising providing a robotic control structure having a support structure, said support structure being adapted and configured to be selectively positionable along a prescribed path by said robotic control structure; providing a viscous material deposition system adapted and configured to control deposition of a viscous material from said viscous material deposition system; providing a load sensor associated with said robotic control structure adapted and configured to determine a load of said viscous material supported by said support structure; and positioning said support structure along said prescribed path, wherein said positioning is controlled at least in part based upon said load.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing robot planning using a process definition graph. One of the methods includes receiving an initial underconstrained process definition graph for one or more robots, wherein the process definition graph is a directed acyclic graph having constraint nodes and action nodes. A plurality of transformers are repeatedly applied to the initial process definition graph, wherein each application of a transformer generates a respective modified process definition graph according to the constraint nodes of the process definition graph, wherein applying the plurality of transformers generates a schedule that specifies which of the one or more robots are to perform which of one or more actions represented by actions nodes according to constraints imposed by the constraint nodes in the process definition graph.