Abstract: Embodiments of the present disclosure provide a service vehicle. In some embodiments, the service vehicle comprises a platform configured to service a container handling vehicle while the service vehicle is on a grid-based rail system of a storage grid of an automated storage system for storing storage containers, and one or more wheel modules, each wheel module configured to move the service vehicle along the grid-based rail system, wherein the platform is mounted on the one or more wheel modules and comprises an enclosure having at least one opening.

Abstract: Methods and apparatus for subterranean guidance are disclosed. A disclosed apparatus to guide a vehicle includes interface circuitry communicatively coupled to a ground penetrating sensor supported by the vehicle, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to calculate, based on output from the ground penetrating sensor, a position of the vehicle relative to a subterranean marker, and guide movement of the vehicle at least partially based on the position of the vehicle relative to the subterranean marker.

Abstract: Autonomous return to dock and docking procedures includes a dock and an unmanned aerial vehicle (UAV). The dock includes a first fiducial and second fiducial. The UAV includes a camera, one or more processors, and one or more memories. The one or more processors configured to execute instructions stored in the one or more memories to determine to use the dock for a landing operation by processing a first image depicting the first fiducial, to determine a UAV placement for the landing operation at the dock by processing a second image depicting the second fiducial, and to perform the landing operation to land the UAV at the dock according to the UAV placement.

Abstract: The present application relates to a control method of an aerial vehicle. The aerial vehicle may comprise a propulsion structure for providing flight power and a spraying apparatus for spraying a material. The control method may comprise determining current target information of the aerial vehicle during a process of the aerial vehicle performing a spraying task, wherein the current target information indicates wind field strength of a downward pressure wind field generated by the propulsion structure; determining, based on the current target information, a desired relative flight altitude of the aerial vehicle corresponding to the current target information relative to the material being sprayed below the aerial vehicle; and controlling the aerial vehicle to fly toward the desired relative flight altitude.

Abstract: A system and method for a digital co-pilot are provided. The method includes receiving a plurality of inputs from a vehicle operating systems, wherein the plurality of inputs comprise engine parameters, control system parameters, or electrical system parameters, identifying one or more first trends in the plurality of inputs, diagnosing one or more first potential conditions based on the first trends, determining a first course of action based on diagnosing the one or more potential conditions, and generating one or more first commands to vehicle controls based on determining the first course of action.

Abstract: Grids representing predictions of wind vectors (or velocities) over a ground region are obtained from a model and downscaled to a greater level of resolution based on surface roughness metrics of the ground region. Observations of wind vectors over the ground region are determined from ground-based or airborne systems and assimilated into the grids. Subsequently, grids representing the assimilated wind vectors at an initial time, and the predictions of wind vectors at future times, are provided as inputs to a machine learning model, such as a gradient-boosted decision trees algorithm, along with the surface roughness metrics and other relevant features. A continuous representation of predicted wind vectors over the ground region generated based on outputs received from the model is utilized to make operational decisions regarding an aerial vehicle.

Abstract: Provided is a control method for an automated guided system including a step of providing an automated guided vehicle including a sensor and a watchdog timer, a controller, and an alarm, an initializing step of initializing a count value, a first checking step of checking an abnormal state of the sensor, a count increasing step of increasing the count value, and a step of performing a recovery operation, the step of performing the recovery operation includes a second checking step of rechecking the abnormal state, a step of turning on the alarm; a third checking step of rechecking the abnormal state, and a step of turning off the alarm.

Abstract: The present invention relates to a safety compliance, identification, and security monitoring system that includes a monitoring device operable to capture images/videos of a predefined area and persons and events within the area. The monitoring device is further operable to determine whether persons within the area are wearing required personal protective equipment. In one embodiment, the monitoring device initiates an alert a safety equipment infraction. In one embodiment, the system is operable to further record an incident report identifying the nature, date, and location of the infraction, as well as the identity of the person committing the infraction. In one embodiment, the system is operable to monitor various external conditions, such as heat, humidity, smoke, and initiate an alert of the external condition detected. In one embodiment, the system detects quality assurance/quality control issues, including situations involving inspecting equipment, tools, and/or materials for non-conformance.

Abstract: A control operation representer of a simulation system for a vehicle represents control operation of a travel controller in accordance with vehicle external detection information outputted by a vehicle external detection controller based on a captured vehicle external image. A vehicle behavior calculator calculates behavior of the vehicle in accordance with the control operation. A vehicle external image generator generates a vehicle external image in accordance with the behavior and displays the vehicle external image on a display member. An imaging member captures the vehicle external image displayed, and outputs a captured vehicle external image to the vehicle external detection controller. The vehicle external detection controller operates in a closed loop including these.

Abstract: A procedure for docking an aerial vehicle at a docking station includes multiple phases. In a first phase, the aerial vehicle begins a descent at a position over a prior position of the docking station, and monitors a pose using navigation sensors and images captured from below the aerial vehicle. The docking station includes visual markings in a pattern. The aerial vehicle detects the markings within the images, and determines poses based on the pattern. When the poses converge, the docking evolution proceeds to a second phase, during which the aerial vehicle determines poses using images and inertial sensors. When the aerial vehicle reaches an altitude below which the markings do not appear within the field of view of the camera, the docking evolution proceeds to a third phase, during which the aerial vehicle determines poses using images, inertial sensors and range data, until the aerial vehicle is docked.

Abstract: Systems and methods for providing autonomous vehicle assistance are disclosed. In one embodiment, a method is disclosed comprising detecting a service condition in response to a fault occurring at an autonomous vehicle at a first location; coordinating service with a nearby service provider, the service provider providing a time window and a second location; predicting that the autonomous vehicle will be free to fulfill the service; driving the autonomous vehicle to the second location of the service provider during the time window; and returning the autonomous vehicle to the first location after the service is completed.

Abstract: A vegetation monitoring device with at least one camera unit (28) for monitoring vegetation health in a garden (10), wherein the at least one camera unit (28) is configured to detect the garden area (30, 32, 34) in at least a first range of the electromagnetic spectrum, in particular in the visible light range, and in at least a second region of the electromagnetic spectrum, in particular in the infrared range, in order to determine at least one vegetation index of at least one garden area (30, 32, 34) of the garden (10), in particular in the region of visible light, and in at least one second region of the electromagnetic spectrum, in particular in the infrared range, wherein the camera unit (28) is provided for an arrangement at least substantially above ground level of the garden (10) and for an at least substantially stationary arrangement outside or in the vicinity of the garden (10), and a vegetation monitoring system is proposed.

Abstract: A construction machine includes a travel actuator, an attachment actuator, a storage, an information obtaining device, and a hardware processor configured to perform braking control of at least one of the travel actuator and the attachment actuator in response to determining that a dangerous situation is going to occur based on information obtained by the information obtaining device and information stored in a database in the storage.

Abstract: A method for adjusting a video image in a vehicle equipped with a driving video recording device, and a vehicle using same, are disclosed. The method may include obtaining, by a camera module of the driving video recording device, video data corresponding to a video depicting surroundings of the vehicle. The method may also include obtaining, by a processor of the driving video recording device, a gravity vector acquired using a G sensor of the driving video recording device. The method may additionally include determining, by the processor, an adjustment value according to the gravity vector acquired using the G sensor. The adjustment value may include one or both of a pitch adjustment value or a roll adjustment value. The method may further include adjusting, by the processor, the video data using the adjustment value to generate adjusted video data. The method may also include displaying, by a head unit of the vehicle, the adjusted video data together with navigation information on a screen.

Abstract: A method of controlling docking for a marine vessel includes imaging an area around a marine vessel with an imaging system to generate image data, generating a display of a docking area on a user interface based on the image data, receiving a user input selecting a location on the display of the docking area, identifying a selected docking location based on the selected location on the display and based on at least one dimension of the marine vessel, and updating the display of the docking area to represent the marine vessel docked at the selected docking location.

Abstract: To provide an information processing apparatus capable of improving the efficiency of operation of a movable apparatus, an information processing apparatus comprises: a passing region calculation unit configured to calculate a passing region through which a movable apparatus passes; an object detection unit configured to detect an object around the movable apparatus by a sensor; and an object detection range setting unit configured to set an object detection range in which the object is detected by the object detection unit based on the passing region calculated by the passing region calculation unit.

Abstract: Techniques for determining a metrics associated with a vehicle are disclosed. The techniques may comprise receiving a driving simulation scenario associated with a simulated vehicle. Based at least in part on the scenario and a dataset of recorded driving associated with operation of a test vehicle, a plurality of driving events present in the dataset may be determined. Based at least in part on the plurality of driving events, a first metric associated with a likelihood of occurrence of the driving simulation scenario may be determined. A simulation may be instantiated based at least in part on the driving simulation scenario. Based at least in part on the simulation, a safety metric indicative of the safe performance of the simulated vehicle in the simulation may be determined. An aggregate safety metric may be determined based at least in part on the safety metric and the first metric.

Abstract: A work machine includes a vehicle body, a travel direction detecting section that detects a travel direction of the vehicle body, an object detecting section that detects an object in a predetermined direction of the vehicle body, a braking section, a setting section. and a control section. The braking section is able to implement automatic braking of the vehicle body and exert a braking force based on a detection of the object. The setting section sets the braking section so that the automatic braking force can be or cannot be exerted. The control section controls the setting section to set the braking section so that the braking force can be exerted when the vehicle body is traveling in the predetermined direction, and to set the braking section so that the braking force cannot be exerted when the vehicle body is traveling in a direction other than the predetermined direction.

Abstract: A hauling vehicle including a vehicle body, a distance meter that measures the distance to an obstacle, an in-vehicle controller that controls the vehicle body, and a communication device that communicates with a management controller that manages the vehicle body is provided.

Abstract: Provided are a surveillance system, an information processing device, a fall detection method, and a non-transitory computer readable medium capable of improving the accuracy of detecting a person who has fallen down in a railroad crossing. A surveillance system according to the present disclosure includes a LiDAR sensor (10) that emits a plurality of laser beams with different ranges to a surveillance area, and outputs a detection signal indicating a detection status of an object by each of the laser beams, and an information processing device (20) that determines that the object has fallen down when the detection status by a laser beam with a shorter range than a predetermined range indicates that the object is detected and the number of laser beams detecting the object decreases.