Abstract: A mobile manipulator includes a moving apparatus, a manipulator that is connected to the moving apparatus, a controller configured to control the moving apparatus and the manipulator, and an environment acquisition sensor configured to acquire predetermined environmental data originating from an environment at the movement destination to which the mobile manipulator is moved by the moving apparatus in association with a position at the movement destination, and the controller controls at least one of the moving apparatus and the manipulator based on the environmental data.

Abstract: An apparatus for fault diagnosis and back-up of advanced driver assistance system sensors based on deep learning, the apparatus including: an individual sensor diagnosis unit configured to quantitatively evaluate a reliability of an output result of each sensor at each moment on the basis of a model for an output of each sensor under a normal operation; an inter-sensor mutual diagnosis unit configured to extract shared representation between the sensors and quantitatively evaluate a normal-operation reliability of the output result of each sensor on the basis of the extracted shared representation; and an integrated diagnosis unit configured to quantitatively evaluate a final reliability of each sensor on the basis of output results of the individual sensor diagnosis unit and the inter-sensor mutual diagnosis unit.

Abstract: An autonomous industrial truck, in particular an order-picking industrial truck, including an undercarriage to support the industrial truck on a roadway. The undercarriage is located on an undercarriage chassis and the industrial truck has a supporting chassis that is provided with supporting means. The supporting chassis can be adjusted relative to the undercarriage chassis between a raised position in which the supporting means are raised from the roadway and a lowered position in which the supporting means are lowered onto the roadway.

Abstract: Systems and methods are provided that employ spatial and temporal attention-based deep reinforcement learning of hierarchical lane-change policies for controlling an autonomous vehicle. An actor-critic network architecture includes an actor network that process image data received from an environment to learn the lane-change policies as a set of hierarchical actions, and a critic network that evaluates the lane-change policies to calculate loss and gradients to predict an action-value function (Q) that is used to drive learning and update parameters of the lane-change policies. The actor-critic network architecture implements a spatial attention module to select relevant regions in the image data that are of importance, and a temporal attention module to learn temporal attention weights to be applied to past frames of image data to indicate relative importance in deciding which lane-change policy to select.

Abstract: Disclosed is a driving assistance apparatus for a vehicle, including: a communication apparatus configured to perform V2X communication with an external device outside of the vehicle; and a processor which is configured to: acquire information about a set path for the vehicle; receive V2V data from one or more other vehicles through the communication apparatus; based on the information about the set path and the one or more V2V data, select, from among the one or more V2V data, data of interest which is V2V data transmitted by a vehicle of interest which is a other vehicle located on the set path; and set a recommended path for the vehicle based on the data of interest.

Abstract: A method is provided for comparing relevant information between observations. Methods may include: receiving first sensor data from a first sensor type; receiving second sensor data from a second sensor of a second sensor type, different from the first sensor type, where the first and second sensor data includes data associated with an environment of the sensors; generating a first binary bitmask of the first sensor data; generating a second binary bitmask of the second sensor data; applying a mutual information score function using the first binary bitmask and the second binary bitmask as inputs; generating a mutual information score from the mutual information score function, wherein the mutual information score represents a degree of similarity between the sensor data; and establishing a reliability of the at least one of the first sensor or the second sensor.

Abstract: Methods, apparatuses and systems for use of a magnetometer calibration (MAG-CAL) application to calibrate a magnetometer while an aircraft is in-flight including: generating a MAG-CAL calculated pattern based on a set of aircraft parameters for the in-air magnetometer calibration, the set of aircraft parameters at least comprise: speed, bank angle, altitude and position of the aircraft; generating a set of waypoints that define a calibration flight path corresponding to the MAG-CAL calculated pattern; Configuring the calibration flight path of the MAG-CAL calculated pattern to be part of the original flight path of the in-flight aircraft to enable the aircraft while flying the original flight to proceed in part on the calibration flight path corresponding to the MAG-CAL calculated pattern; and enabling the aircraft to deviate while in-flight from the original flight path to the calibration flight path to enable a sufficient level of calibration for accurate magnetometer operation.

Abstract: The system for aiding the landing of an aircraft on a landing runway of an airport equipped with an Instrument Landing System (“ILS”) corresponding to an axis of a predetermined approach, includes: an ILS signals receiver and a processing unit. The processing unit is configured to, when the ILS signals receiver) has not yet captured a Glide signal corresponding to a Glide axis of the approach as a function of items of information relating to the predetermined approach, acquired from a database, determine a protection volume in which there is no risk of the ILS signals receiver detecting a replica of the Glide signal; and when a current position of the aircraft is above the protection volume, inhibit the capture of the Glide signal by the ILS signals receiver and instruct the emission of an alert item of information in the cockpit of the aircraft.

Abstract: A method for controlling brakes includes receiving, by a controller, a first wheel speed from a first wheel speed sensor of a first wheel arrangement, receiving, by the controller, a second wheel speed from a second wheel speed sensor of a second wheel arrangement, calculating, by the controller, a pressure correction, and adjusting, by the controller, a pressure command for at least one of the first wheel arrangement and the second wheel arrangement.

Abstract: Methods and systems are provided for navigating to a pre-scheduled vehicle. A code is analyzed for a user including location information pertaining to the pre-scheduled vehicle, wherein the location information indicates a destination for the user. A location of the user is determined based on a GPS sensor. The user is directed to traverse a route between the location of the user and a location of the pre-scheduled vehicle. A destination of the pre-scheduled vehicle is verified as being consistent with the destination for the user indicated by the location information of the code.

Abstract: A method of operating an autonomous cleaning robot is described. The method includes initiating a training run of the autonomous cleaning robot and receiving, at a mobile device, location data from the autonomous cleaning robot as the autonomous cleaning robot navigates an area. The method also includes presenting, on a display of the mobile device, a training map depicting portions of the area traversed by the autonomous cleaning robot during the training run and presenting, on the display of the mobile device, an interface configured to allow the training map to be stored or deleted. The method also includes initiating additional training runs to produce additional training maps and presenting a master map generated based on a plurality of stored training maps.

Abstract: An intelligent vehicle charging system for charging a fleet of autonomous vehicles throughout a network of charging stations dispersed throughout a geographic area. The intelligent vehicle charging system includes a remote control system that is in operative communication with each of the autonomous vehicles in the fleet and each of the charging stations in the network. When an autonomous vehicle is in need of a power charge, or as directed by the remote control system, the remote control system will identify an available charging station, guide the autonomous vehicle to the charging station, verify that the autonomous vehicle has arrived at the charging station, initiate the power charging process, account and bill appropriate fees for the charging process, and log all associated activity. The remote control system is also capable of remotely and instantaneously terminating the power charging process to dynamically return a vehicle back to service.

Abstract: A method and a device for automatically reversing a vehicle are provided. A forward track of a target vehicle is recorded in a forward process of the target vehicle. The target vehicle is controlled to be reversed from a current position and the target vehicle is controlled to be reversed along the forward track by adjusting a steering wheel angle of the target vehicle at each reversing moment, when an automatic reversing instruction for the target vehicle is detected after the target vehicle stops moving forward. The target vehicle is controlled to stop being reversed when a reversing stop instruction for the target vehicle is detected in a reversing process.

Abstract: A control system for an agricultural implement includes a controller configured to perform the following steps in response to determining that performance of a ground engaging tool is below a threshold performance. The controller is configured to adjust a speed of the agricultural implement to an adjusted speed. The controller is configured to raise the ground engaging tool to a target raised position in response to the speed of the agricultural implement being substantially equal to a first threshold speed. The controller is configured to adjust the speed of the agricultural implement to an initial speed in response to a position of the ground engaging tool being substantially equal to the target raised position. The controller is configured to lower the ground engaging tool to a target depth in response to the speed of the agricultural implement being substantially equal to a second threshold speed.

Abstract: A set of driving scenarios are determined for different types of vehicles. Each driving scenario corresponds to a specific movement of a particular type of autonomous vehicles. For each of the driving scenarios of each type of autonomous vehicles, a set of driving statistics is obtained, including driving parameters used to control and drive the vehicle, a driving condition at the point in time, and a sideslip caused by the driving parameters and the driving condition under the driving scenario. A driving scenario/sideslip mapping table or database is constructed. The scenario/sideslip mapping table includes a number of mapping entries. Each mapping entry maps a particular driving scenario to a sideslip that is calculated based on the driving statistics. The scenario/sideslip mapping table is utilized subsequently to predict the sideslip under the similar driving environment, such that the driving planning and control can be compensated.

Abstract: An aircraft controller includes a memory for storing instructions. The instructions are operable to cause the controller to perform a thrust balancing method and ensure a balanced thrust output from the aircraft.

Abstract: A vehicle includes a drivetrain and multiple motors. The drivetrain includes at least one wheel, and is mechanically connected to the motors. The vehicle additionally includes multiple control modules communicatively connected to the motors. The control modules include a power control module per motor. Each power control module is assigned a motor, communicatively connected to the assigned motor, and configured to operate the assigned motor. In response to a traction event, the control modules are configured to switch from a drive mode to a traction control mode. In the drive mode, the power control modules are configured to operate the respective assigned motors to contributorily satisfy at least one propulsion demand global to the vehicle. In the traction control mode, one of the control modules is configured to operate the motors to contributorily satisfy at least one propulsion demand global to the vehicle.

Abstract: Apparatus and methods for machine-based planning. The apparatus may cluster a plurality of geographically different resources into a plurality of clusters of proximate resources. The apparatus may calculate a cost of transporting each resource to each of a plurality of destinations. The apparatus may map each cluster to one of the destinations to determine a sum of costs of transporting all of the resources to the destinations. The apparatus may assign to each of the plurality of destinations only resources: that are mapped to the destination; for which the destination has sufficient capacity to accommodate the resources; and whose assignment to the destination does not exclude from the destination, by filling the capacity, a different resource that is: mapped to the destination; and has a net cost that is higher than a net cost of the resource of the assignment.

Abstract: A system includes one or more processors configured to obtain environmental data geographically and temporally corresponding to scheduled travel of a vehicle system. The one or more processors are further configured to determine a power output capability range for the vehicle system traveling during a trip based on the environmental data that is obtained. The one or more processors are also configured to communicate instructions to at least one of a propulsion system of the vehicle system or a vehicle controller of the vehicle system for controlling movement of the vehicle system during the trip such that the vehicle system produces a power output within the power output capability range as the vehicle system travels. The environmental data includes historical values of one or more of temperature, pressure, or air constituency in geographic areas through which the vehicle system will travel during the trip.

Abstract: A method for controlling a multi-speed transmission for an engine powering a marine propulsion device on a marine vessel is disclosed. The method is carried out by a control module and includes determining a load of the engine, determining speed of the engine, and determining a pitch of the marine vessel. The method includes switching between a first gear ratio and a second gear ratio of the transmission based on the engine load, the engine speed, and the vessel pitch.