Abstract: A control method includes: deriving an approach location at which the end effector grips an operation object; deriving a scan location for scanning an identifier of the operation object; and based on the approach location and the scan location, creating or deriving a control sequence to instruct the robot to execute the control sequence. The control sequence includes (1) gripping the operation object from a start location; (2) scanning an identifier of the operation object with a scanner located between the start location and a task location; (3) temporarily releasing the operation object from the end effector and regripping the operation object by the end effector to be shifted, at a shift location, when a predetermined condition is satisfied; and (4) moving the operation object to the task location.

Abstract: A belt drive system includes a driving wheel, a driven wheel and a drive belt. A first and a second drive belt tensioning mechanism are included. When a first drive member rotates, it moves relative to a first mounting seat and along an axial direction of the first drive member to drive the first tensioning device to move relative to the housing. When a second drive member rotates, it drives the second tensioning device to move relative to the second mounting seat. A related automatic walking robot includes a housing, a road wheel set rotatably arranged on the housing, and a walking motor arranged on the housing for driving the road wheel set.

Abstract: In one or more embodiments, one or more systems, methods, and/or processes may determine that a first vehicle is unsafe to continue navigating to the drop-off location while the first vehicle is traveling en-route to transport one or more passengers to a drop-off location. Based on this determination, an intermediate area for the one or more passengers to be dropped off by the first vehicle and picked up by a second vehicle is determined. Instructions are then provided to the first vehicle to cause the first vehicle to navigate to the intermediate area. Further, instructions are provided to the second vehicle to navigate at least in proximity to the intermediate area to pick up the one or more passengers, and navigate to the drop-off location after picking up the one or more passengers.

Abstract: Technologies for sharing route navigation data in a community cloud include a mobile navigation device of a vehicle and a remote mobile navigation device of a remote vehicle. The mobile navigation device generates sensor data associated with a current route of the vehicle and determines whether a reference traffic event occurs within a segment of the current route of the vehicle. In response to a determination that a reference traffic event occurs, the mobile navigation devices transmits route update data to the remote mobile navigation device. Based on the route update data, the remote mobile navigation device updates a current route of the remote vehicle to avoid the reference traffic event within a corresponding segment of the current route of the remote vehicle. The mobile navigation device may also transmit the sensor data to a community compute device, which may transmit route update data to the remote mobile navigation device.

Abstract: Disclosed are a method and a system for multi-objective optimization of urban train operation. Firstly, speed limit information, slope information and curve radius information of a real train route are obtained, a section is segmented into non-equal sub-sections according to the above information about actual line characteristics, and then a longitudinal dynamics model of the train is constructed in combination with basic vehicle data of the train. Next, energy consumption of the train operation, section operation time, actual parking positions, and rates of acceleration change are calculated, so as to construct a multi-objective optimization model of train operation. Afterwards, a multi-objective differential evolution algorithm is used to solve the multi-objective optimization model, in order to obtain a Pareto optimal solution set of each operation district. Finally, an optimal solution is obtained which takes all objectives into comprehensive consideration, and an optimal train speed curve is generated.

Abstract: An actuator according to an aspect of the present invention includes: a driving body including a plurality of conductive grains, a chamber configured to confine the plurality of conductive grains, and two or more electrodes disposed on a surface of the chamber; and a controller configured to obtain, through the two or more electrodes, a change in an electric signal, in response to a load applied to the chamber, and to adjust the load applied to the chamber based on the change in the electric signal.

Abstract: Enclosed are embodiments for sampling driving scenarios for training machine learning models. In an embodiment, a method comprises: assigning, using at least one processor, a set of initial physical states to a set of objects in a map for a set of simulated driving scenarios, wherein the set of initial physical states are assigned according to one or more outputs of a random number generator; generating, using the at least one processor, the set of simulated driving scenarios in the map using the initial physical states of the objects in the set of objects; selecting, using the at least one processor, samples of the simulated driving scenarios; training, using the at least one processor, a machine learning model using the selected samples; and operating, using a control circuit, a vehicle in an environment using the trained machine learning model.

Abstract: A control apparatus, comprising: an image obtaining unit configured to obtain an image in which a control target that a robot controls and a target position to which the control target is to be moved are imaged by an imaging apparatus that is attached to the robot; an axial direction obtainment unit configured to obtain an axial direction of a rotational axis of the control target; a target position detection unit configured to detect the target position in the image; an operation generation unit configured to generate an operation for the control target so that the target position is present in the axial direction and to further generate an operation by which the control target becomes closer to the target position in the axial direction; and a control unit configured to control the control target in accordance with the operation.

Abstract: A command model connected to plurality of flight components of an electric aircraft and comprises a circuitry configured to detect a predicted state and a measured state datum, transmit predicted state datum to an actuator model, and transmit measured state datum to a plant model. An actuator model connected to the sensor configured to receive the predicted state datum and generate a performance datum. A plant model connected to the sensor configured to receive measured state datum and performance datum from the actuator model, transmit a feedback path to controller, and generate an inconsistency datum as a function of the measured state datum and the performance datum. A controller communicatively connected to the sensor, wherein the controller is configured to receive the inconsistency datum from the plant model and apply a torque to the aircraft as a function of the inconsistency datum.

Abstract: A mobile robot configured to travel across a residential floor or other surface while cleaning the surface with a cleaning pad and cleaning solvent is disclosed. The robot includes a controller for managing the movement of the robot as well as the treatment of the surface with a cleaning solvent. The movement of the robot can be characterized by a class of trajectories that achieve effective cleaning. The trajectories include sequences of steps that are repeated, the sequences including forward and backward motion and optional left and right motion along arcuate paths.

Abstract: A method includes the step of receiving traffic signal display information from a traffic control unit controlling a display of a traffic signal located near an intersection when a vehicle is driving toward the intersection. The traffic signal display information includes a current display state of the traffic signal and information indicating a remaining time for which the current display state of the traffic signal will continues. The method further includes the step of acquiring traffic signal recognition information when the vehicle is driving toward the intersection. The traffic signal recognition information is recognized by a traffic signal detector mounted on the vehicle and indicating a current display of the traffic signal. The method further includes the step of controlling driving of the vehicle when the vehicle enters the intersection based on the traffic signal display information and the traffic signal recognition information.

Abstract: A complicated motion program is taught, in a simple manner, to a lead-through teachable robot. Provided is a teaching apparatus for a robot, the teaching apparatus being provided with: a movement-instruction input portion that is attached to the robot and with which a movement instruction for the robot is input; and a command input portion with which it is possible to set at least one of a movement-trajectory defining command, a standby command, a speed-changing command, and a work-condition changing command at an arbitrary position on a movement pathway of the robot in a direction that corresponds to the movement instruction input via the movement-instruction input portion.

Abstract: A robot system according to the present invention comprises a control apparatus for controlling a robot, and a video display apparatus connected to the control apparatus. The video display apparatus comprises a display unit which displays an image of a real space containing the robot, in real time as the image is taken by a camera, and an augmented reality image processing unit which causes a virtual image of an end effector or robot peripheral equipment of the robot to be displayed on the display unit in superimposed fashion on a real image of the robot taken by the camera. According to the robot system, even when the end effector or the robot peripheral equipment is not present, a robot teaching task can be performed by assuming that they are present.

Abstract: Provided is a robot device including an image input unit for inputting an image of surroundings, a target object detection unit for detecting an object from the input image, an object position detection unit for detecting a position of the object, an environment information acquisition unit for acquiring surrounding environment information of the position of the object, an optimum posture acquisition unit for acquiring an optimum posture corresponding to the surrounding environment information for the object, an object posture detection unit for detecting a current posture of the object from the input image, an object posture comparison unit for comparing the current posture of the object to the optimum posture of the object, and an object posture correction unit for correcting the posture of the object when the object posture comparison unit determines that there is a predetermined difference or more between the current posture and the optimum posture.

Abstract: Simulating realistic movement of an object, such as a vehicle or pedestrian, that accounts for unusual behavior may comprise generating an agent behavior model based at least in part on output of a perception component of an autonomous vehicle and determining a difference between the output and log data that includes indications of an actual maneuver of location of an object. Simulating movement of an object may comprise determining predicted motion of the object using the perception component and modifying the predicted motion based at least in part on the agent behavior model.

Abstract: A robot control system according to an embodiment is a control system for a robot comprising an arm, the arm being capable of holding a tool while rotating the tool and capable of moving the tool in at least two-dimensional directions, the arm being equipped with a rotating mechanism provided for the tool. The robot control system comprises a load-acquiring unit and a control-signal-generating unit. The load-acquiring unit is configured to acquire a force measured by a force sensor configured to measure a force applied from the tool to the arm during profile copying performed on a machining object by moving the arm while a copying guide attached to the arm and a copying mold placed on the machining object are kept in contact with each other.

Abstract: Apparatus and methods for training and operating of robotic devices. Robotic controller may comprise a predictor apparatus configured to generate motor control output. The predictor may be operable in accordance with a learning process based on a teaching signal comprising the control output. An adaptive controller block may provide control output that may be combined with the predicted control output. The predictor learning process may be configured to learn the combined control signal. Predictor training may comprise a plurality of trials. During initial trial, the control output may be capable of causing a robot to perform a task. During intermediate trials, individual contributions from the controller block and the predictor may be inadequate for the task. Upon learning, the control knowledge may be transferred to the predictor so as to enable task execution in absence of subsequent inputs from the controller. Control output and/or predictor output may comprise multi-channel signals.

Abstract: The present invention discloses a method and flight controller for controlling an aircraft, comprising the following step: —determining the pitch control input ?E for at least one pitch moment generator element, based on the lift control input ?F for at least one lift generator element; wherein the step of determining the pitch control input ?E based on the lift control input ?F includes the step of determining a feed forward filter output Fq,?E,?F(q).

Abstract: Deep machine learning methods and apparatus related to the manipulation of an object by an end effector of a robot are described herein. Some implementations relate to training an action prediction network to predict a probability density which can include candidate actions of successful grasps by the end effector given an input image. Some implementations are directed to utilization of an action prediction network to visually servo a grasping end effector of a robot to achieve a successful grasp of an object by the grasping end effector.

Abstract: The present disclosure provides methods and systems for operating a rotorcraft comprising a plurality of engines configured to provide motive power to the rotorcraft and at least one rotor coupled to the plurality of engines. Failure of an active engine of the rotorcraft is detected when the rotorcraft is operated in an asymmetric operating regime (AOR), in which at least one first engine of the plurality of engines is the active engine and is operated in an active mode to provide motive power to the rotorcraft and at least one second engine of the plurality of engines is a standby engine and is operated in a standby mode to provide substantially no motive power to the rotorcraft. At least one flight control input is adjusted to compensate for a reduction in rotational speed of the at least one rotor resulting from the failure of the active engine. An increase in a power output of the standby engine of the rotorcraft is commanded.