Abstract: A vehicle control device is configured to issue a command to change at least a behavior of a vehicle in accordance with a change in a driving situation of the vehicle, and includes a vehicle condition detection device, an image capture device, a display device, and an arithmetic control device. The vehicle condition detection device is a slope angle detection sensor to measure a slope angle of a road surface on which the vehicle is driving. The image capture device is configured to capture an image of an area ahead of the vehicle. The display device is configured to display an image in a vehicle compartment of the vehicle. The arithmetic control device is configured to display the image of the area ahead of the vehicle on the display device when an amount of change in the slope angle measured by the vehicle condition detection device exceeds a predetermined threshold.

Abstract: Aspects of the disclosure relate to arranging a pick up and drop off locations between a driverless vehicle and a passenger. As an example, a method of doing so may include receiving a request for a vehicle from a client computing device, wherein the request identifies a first location. Pre-stored map information and the first location are used to identify a recommended point according to a set of heuristics. Each heuristic of the set of heuristics has a ranking such that the recommended point corresponds to a location that satisfies at least one of the heuristics having a first rank and such that no other location satisfies any other heuristic of the set of heuristics having a higher rank than the first rank. The pre-stored map information identifying a plurality of pre-determined locations for the vehicle to stop, and the recommended point is one of the plurality of pre-determined locations.

Abstract: A method of using a cleaning robot for improved cleaning of edges of a wall having a projecting baseboard, includes using the robot to strike the baseboard in a first cleaning pass, causing an impact sensor to generate a first signal and a distance sensor to detect a first distance from the wall. The robot continues its first cleaning pass and strikes the baseboard a further time, causing the impact sensor to generate a second signal and the distance sensor to detect a second distance from the wall. A computer of the robot uses the signals to calculate two spatial points and a first straight line running through the points. The computer uses the distances and the two spatial points to establish an approach boundary of the cleaning robot relative to the wall. The computer controls the cleaning robot during subsequent cleaning passes exclusively using the one distance sensor.

Abstract: A method and computing system for transferring objects between a source repository and a destination repository is provided. The computing system is configured to operate by a combination of pre-planned and image base trajectories to improve speed and reliability of object transfer. The computing system is configured to capture image information of repositories and use the captured information to alter or adjust pre-planned trajectories to improve performance.

Abstract: A navigation control system for an autonomous vehicle comprises a transmitter and an autonomous vehicle. The transmitter comprises an emitter for emitting at least one signal, a power source for powering the emitter, a device for capturing wireless energy to charge the power source, and a printed circuit board for converting the captured wireless energy to a form for charging the power source. The autonomous vehicle operates within a working area and comprises a receiver for detecting the at least one signal emitted by the emitter, and a processor for determining a relative location of the autonomous vehicle within the working area based on the signal emitted by the emitter.

Abstract: A robotic system is disclosed. The system includes a memory that stores for each of a plurality of items a set of attribute values. The system includes a processor(s) that uses the attribute values to simulate the placement of items, including by determining, iteratively, for each next item a placement location at which to place the item on a simulated stack of items on the pallet, using the attribute values and a geometric model of where items have been simulated to have been placed to estimate a state of the stack after each of a subset of simulated placements, and using the estimated state to inform a next placement decision. The steps of determining for each next item a placement location and estimating the state of the stack until all of at least a subset of the plurality of items have been simulated as having been placed on the stack.

Abstract: The robot includes a storage unit and a control unit. The control unit acquires outside stimulus feature amounts that are feature amounts of an outside stimulus acting from outside, stores the acquired outside stimulus feature amounts in the storage unit as a history, compares outside stimulus feature amounts acquired at a certain timing with outside stimulus feature amounts stored in the storage unit to calculate a first similarity degree, and controls operations based on the calculated first similarity degree.

Abstract: A method for changing or expanding application tasks of a manipulator via a first processor and a second processor and a system for guiding the movement of the manipulator, wherein the system includes a first processor for performing control tasks relating to guiding the movement, the control tasks being performable in real-time and being performable while complying with pre-definable, in particular certifiable, safety requirements, and includes at least one second processor for performing an application task formed from a path planning task and a task relating to processing user inputs, where the second processor can be adapted to perform at least one changed or further application task.

Abstract: An autonomous cleaning robot includes a drive system to support the autonomous cleaning robot above a floor surface, an image capture device positioned on the autonomous cleaning robot to capture imagery of a portion of the floor surface forward of the autonomous cleaning robot, and a controller operably connected to the drive system and the image capture device. The drive system is operable to maneuver the autonomous cleaning robot about the floor surface. The controller is configured to execute instructions to perform operations including initiating, based on a user-selected sensitivity and the imagery captured by the image capture device, an avoidance behavior to avoid an obstacle on the portion of the floor surface.

Abstract: The embodiments of the present disclosure provide a method of travel control, a device and a storage medium. In some exemplary embodiments of the present disclosure, a self-mobile device collects three-dimensional environment information on a travel path of itself in the travel process, identifies an obstacle area and a type thereof existing on the travel path of the self-mobile device based on the three-dimensional environment information, and the self-mobile device adopts different travel controls in a targeted manner for different types of the area, such that the obstacle avoidance performance of the self-mobile device is improved by adopting the method of the travel control in the present disclosure.

Abstract: Autonomous carriers or totes that include vacuum units are provided. As the totes move or are moved through a warehouse carrying products, they collect debris. The debris can be analyzed at the tote, and actions can be performed based upon the analysis.

Abstract: A mobile robot system and method for determining the stiffness of a human arm while moving with a user during overground interaction as the user holds the robot's handle and exchanges forces with it. A mobile base moves with the user, a robot arm interacts with the user, and a controller determines the stiffness. The robot arm includes servomotors driving a linkage mechanism, an end effector including the handle supported by the linkage mechanism, and a force transducer measuring a force applied by the user to the handle. The controller causes the robot arm to generate a force perturbation at the handle, measure a peak velocity achieved by the human arm, determine the stiffness of the human arm as a function of force and displacement, and control operation of the system based on the determined stiffness. A robot body may allow for adjusting the height of the robot arm.

Abstract: A method for moving along a predetermined path with a robot in an at least a partially automated manner includes determining a deployment position on a current path section of the predetermined path for which a distance parameter satisfies a predetermined condition, and moving to the deployment position with the robot. In one aspect, the robot may be moved to the deployment position if a deployment condition is satisfied. The distance parameter may be determined on the basis of a distance of a current position of the robot relative to the current path section. The predetermined condition may be that the distance parameter has a value that is less than or equal to the values of the distance parameter of all positions in a partial area of the current path section, which is in particular complementary to the deployment position.

Abstract: A system is for remote calibration and testing of a vehicle including a plurality of sensors and a data collection and transmission unit (“DCTU”). The system includes a receiving station and at least one virtual reality station. The receiving station is configured to establish a communication gateway between the DCTU and the at least one virtual reality station. The virtual reality station is configured to give a virtual vehicular experience by rendering data received from the DCTU on a plurality of actuators and a digital twin of the vehicle. Based on a physical experience and a recorded output in the at least one virtual reality station, an expert provides feedback to the DCTU via the receiving station for calibration and testing of the vehicle.

Abstract: A method for controlling a driving dynamics function of a working machine with at least two vehicle axles. A current actual wheel rotational speed of at least one wheel is detected and sent to a control unit for comparison with an acceptable wheel rotational speed of the same wheel and wheel slip is calculated from that comparison. The control unit emits a control signal to lock at least one differential gear system if the wheel slip has an unacceptable value. For the differential gear system (4, 5, 6, 7, 8) concerned, an unlocking control signal is periodically emitted and the wheel rotational speeds are compared afresh. A control signal to lock the differential gear system concerned is emitted again if the value of the wheel slip is still unacceptable, and a trajectory is detected with reference to detection elements, along which the value of the wheel slip of the at least one wheel has been unacceptable.

Abstract: A method for using a control center at a remote site to control operation of a robotic medical device system at a local site includes transmitting a control signal from the control center to the robotic medical device system, determining a delay in transmission of the control signal, comparing the delay to a threshold delay value and operating the robotic medical device system based on the comparison of the delay to the threshold delay value.

Abstract: A method, performed by a cleaning robot, of performing a task, is provided. The method includes capturing an image of an object in a vicinity of the cleaning robot, determining a task to be performed by the cleaning robot, by applying the captured image to at least one trained artificial intelligence (AI) model, controlling a guard portion to descend from in front of an opened portion to a floor surface of the cleaning robot, according to the determined task, and driving towards the object so the object is moved by the descended guard portion.

Abstract: A robot control device is configured to include: a moving route acquiring unit to acquire a moving route of a robot from a first learning model by giving, to the first learning model, observation data indicating a position of an obstacle being present in a region where the robot moves and state data indicating a moving state of the robot at a movement start point at which the robot starts moving among moving states of the robot in the region where the robot moves; and a control value generating unit to generate a control value for the robot, the control value for allowing the robot to move along the moving route acquired by the moving route acquiring unit.

Abstract: Adaptive navigation techniques are disclosed that allow navigation systems to learn from a user's personal driving history. As a user drives, models are developed and maintained to learn or otherwise capture the driver's personal driving habits and preferences. Example models include road speed, hazard, favored route, and disfavored route models. Other attributes can be used as well, whether based on the user's personal driving data or driving data aggregated from a number of users. The models can be learned under explicit conditions (e.g., time of day/week, driver ID) and/or under implicit conditions (e.g., weather, drivers urgency, as inferred from sensor data). Thus, models for a plurality of attributes can be learned, as well as one or more models for each attribute under a plurality of conditions. Attributes can be weighted according to user preference. The attribute weights and/or models can be used in selecting a best route for user.

Abstract: A robot system including: a robot that grips one of a first and second workpiece that are disposed adjacent to each other; an illumination device that radiates light beam onto surfaces of the first workpiece and the second workpiece on either side of a border between the workpieces along a plane that intersects the border; a camera that captures an image containing a first line image of the light beam formed on the surface of the first workpiece and a second line image of the light beam formed on the surface of the second workpiece; and a robot controller that operates the robot based on a misalignment amount and direction of the second line image with respect to the first line image in the image acquired and that performs a correction of a level difference between the surface of the first workpiece and the surface of the second workpiece.