Abstract: Provided are autonomous vehicles and methods of controlling autonomous vehicles through topological planning with bounds, including receiving map data and sensor data, expanding a topological tree by adding a plurality of nodes to represent a plurality of actions associated with the plurality of constraints, generating a bound based on a constraint in the geographic area, the bound associated with an action for navigating the autonomous vehicle relative to the at least one constraint, storing the bound in a central bound storage, linking a set of bounds of a tree node to the bound via a bound identifier, wherein the first bound is initially linked as an active bound, or alternatively, as an inactive bound after determining it is not the most restrictive bound at any sample index, and control the autonomous vehicle based on the topological tree, to navigate the plurality of constraints.

Abstract: A programmable motion robotic system is disclosed that includes a plurality of arm sections that are joined one to another at a plurality of joints to form an articulated arm, and a hose coupling an end effector of the programmable motion robotic system to a vacuum source. The hose is attached to at least one arm section of the articulated arm by a pass-through coupling that permits the hose to pass freely through the coupling as the plurality of arm sections are moved about the plurality of joints.

Abstract: According to some embodiments, a method includes: receiving an endpoint impedance matrix representing a desired stiffness or damping at the robot endpoint; reflecting the endpoint impedance matrix to an equivalent joint-space matrix associated with one or more of the robot joints, the equivalent joint-space matrix having a nullspace corresponding to near-zero-valued eigenvalues; generating a nullspace-filled impedance matrix from the equivalent joint-space matrix based in part on replacing the near-zero-valued eigenvalues with selected finite positive real values; generating a robot control law using the nullspace-filled impedance matrix; and using the robot control law to control the robot.

Abstract: There is provided a mobile robot that performs the obstacle avoidance, positioning and object recognition according to image frames captured by the same optical sensor. The mobile robot includes an optical sensor, a light emitting diode, a laser diode and a processor. The processor identifies an obstacle and a distance thereof according to image frames captured by the optical sensor when the laser diode is emitting light. The processor further performs the positioning and object recognition according to image frames captured by the optical sensor when the light emitting diode is emitting light.

Abstract: The disclosure provides a method for generating a joint command. The method includes receiving a maneuver script including a plurality of maneuvers for a legged robot to perform where each maneuver is associated with a cost. The method further includes identifying that two or more maneuvers of the plurality of maneuvers of the maneuver script occur at the same time instance. The method also includes determining a combined maneuver for the legged robot to perform at the time instance based on the two or more maneuvers and the costs associated with the two or more maneuvers. The method additionally includes generating a joint command to control motion of the legged robot at the time instance where the joint command commands a set of joints of the legged robot. Here, the set of joints correspond to the combined maneuver.

Abstract: Embodiments of the disclosure provide methods and systems for positioning a vehicle. The system may include a communication interface configured to receive a set of point cloud data with respect to a scene captured under a first lighting condition by at least one sensor. The system may further include a storage configured to store the set of point cloud data, and a processor. The processor may be configured to simulate illumination of the scene under a second lighting condition different from the first lighting condition based on the set of point cloud data, modify the set of point cloud data based on the simulated illumination of the scene under the second lighting condition, and position the vehicle under the second lighting condition based on the modified set of point cloud data.

Abstract: A guidance system S includes a plurality of autonomous mobile robots (1) which guide a user to a destination, and a reception apparatus (2) which is provided separately from the robots (1) and recognizes the destination. Availability of each of the plurality of robots (1) is managed based on a state of the robot and the destination.

Abstract: A steering control device includes control circuitry configured to perform synchronization control.

Abstract: A method in a navigational controller includes: controlling a ceiling-facing camera of a mobile automation apparatus to capture a stream of images of a facility ceiling; activating a primary localization mode including: (i) detecting primary features in the captured image stream; and (ii) updating, based on the primary features, an estimated pose of the mobile automation apparatus and a confidence level corresponding to the estimated pose; determining whether the confidence level exceeds a confidence threshold; when the confidence level does not exceed the threshold, switching to a secondary localization mode including: (i) detecting secondary features in the captured image stream; (ii) updating the estimated pose and the confidence level based on the secondary features; and (iii) searching the image stream for the primary features; and responsive to detecting the primary features in the image stream, re-activating the primary localization mode.

Abstract: Aspects of the present invention disclose a method for routing one or more autonomous vehicles to minimize a density of autonomous vehicles and passengers passing through network areas with oversubscribed bandwidth. The method includes one or more processors determining a bandwidth requirement of a first autonomous vehicle. The method further includes determining respective bandwidth requirement for one or more additional autonomous vehicles utilizing a wireless network. The method further includes determining a total bandwidth capacity of one or more nodes of the wireless network. The method further includes determining routing instructions from a current location of the first autonomous vehicle to a destination of the first autonomous vehicle based at least in part on the bandwidth requirement of the first autonomous vehicle and the total bandwidth capacity of the one or more nodes of the wireless network.

Abstract: An autonomous mobile robot includes a chassis, a drive supporting the chassis above a floor surface in a home and configured to move the chassis across the floor surface, a variable height member being coupled to the chassis and being vertically extendible, a camera supported by the variable height member, and a controller. The controller is configured to operate the drive to navigate the robot to locations within the home and to adjust a height of the variable height member upon reaching a first of the locations. The controller is also configured to, while the variable height member is at the adjusted height, operate the camera to capture digital imagery of the home at the first of the locations.

Abstract: A vehicle steering intervention system and method prevents a loss of vehicle control condition or a vehicle rollover condition. The system includes a driver input torque sensor for sensing torque applied by a driver to a steering wheel, a steering angle sensor for sensing a steering angle, and a speed determination device for determining a vehicle speed. An electronic power steering unit includes an electronic processor and a memory. The electronic power steering unit determines a vehicle steering intervention threshold based on the torque sensed, the steering angle, and the vehicle speed. The electronic power steering unit predicts whether the vehicle steering intervention threshold will be exceeded within a predetermined time based on a torque gradient and/or a steering angle gradient. When the vehicle steering intervention threshold is predicted to be exceeded, the electronic power steering unit reduces a power steering assist and/or provides a counter steer force.

Abstract: Implementations are described herein for single iteration, multiple permutation robot simulation. In various implementations, one or more poses of a simulated object may be determined across one or more virtual environments. A plurality of simulated robots may be operated across the one or more virtual environments. For each simulated robot of the plurality of simulated robots, a camera transformation may be determined based on respective poses of the simulated robot and simulated object in the particular virtual environment. The camera transformation may be applied to the simulated object in the particular virtual environment of the one or more virtual environments in which the simulated robot operates. Based on the camera transformation, simulated vision data may be rendered that depicts the simulated object from a perspective of the simulated robot. Each of the plurality of simulated robots may be operated based on corresponding simulated vision data.

Abstract: A control system controls an operation mode of a mobile robot that autonomously moves in a predetermined area, and includes a feature detection unit, a classifying unit, and a system controller. The feature detection unit detects features of a person who is present in the vicinity of the mobile robot. The classifying unit classifies the person into a predetermined first group or a predetermined second group based on the features. The system controller selects a first operation mode when the person who belongs to the first group is present in the vicinity of the mobile robot and selects a second operation mode that is different from the first operation mode when the person who belongs to the first group is not present in the vicinity of the mobile robot, thereby controlling the mobile robot.

Abstract: A robot cleaner for performing cleaning using artificial intelligence includes a suction unit configured to suction dust, a driving unit to drive the robot cleaner, a memory configured to store a compensation model for inferring optimal suction output and driving output for cleaning environment information for learning, and a processor configured to acquire cleaning environment information, determine a suction output value and a driving speed of the robot cleaner from the acquired cleaning environment information using the compensation model, control the suction unit to suction the dust with the determined suction output value, and control the driving unit to drive the robot cleaner at the determined driving speed.

Abstract: A cleaning robot is provided. The cleaning robot includes a motion device configured to move the cleaning robot in an environment, and an exterior housing. The cleaning robot also includes a motion sensor configured to obtain parameters relating to a motion of the cleaning robot, and a storage device configured to store data including at least one of the one or more images or the one or more motion parameters. The cleaning robot also includes a camera configured to capture one or more images of the environment. The camera is disposed internal to a slant surface located at a front end of the exterior housing and is pivotable relative to the slant surface. The slant surface inclines upwardly with respect to a forward moving direction. The camera and the slant surface face substantially a same direction. A direction of the camera and the forward moving direction form an acute angle.

Abstract: Provided is a tangible, non-transitory, machine readable medium storing instructions that when executed by a processor of a robot effectuates operations including: capturing, with at least one sensor, first data used in indicating a position of the robot; capturing, with at least one sensor, second data indicative of movement of the robot; recognizing, with the processor of the robot, a first area of the workspace based on at least one of: a first part of the first data and a first part of the second data; generating, with the processor of the robot, a first movement path covering at least part of the first recognized area; actuating, with the processor of the robot, the robot to move along the first movement path; and generating, with the processor of the robot, a map of the workspace based on at least one of: the first data and the second data.

Abstract: The present disclosure provides a redundant robotic arm control method, a redundant robotic arm, and a computer readable storage medium. The method includes: obtaining an external force acting on an end of the robotic arm and an external torque acting on each joint; calculating a first joint speed of each joint based on a degree of influence of the joint on the end in each motion dimension and the external force acting on the end; determining a zero space speed of each joint corresponding to a current position of the end based on a link torque of an external force acting on a link with respect to the joint; calculating a total joint speed based on the first joint speed and the zero space speed; and controlling the robotic arm to the move according to the total joint speed.

Abstract: Detecting off-zone crashes involving a vehicle using lateral acceleration values detected at locations within the vehicle. In one example method, an electronic processor receives a first acceleration value at a centerline of the vehicle from a first acceleration sensor of at least two acceleration sensors. The electronic processor also receives a second acceleration value at the centerline of the vehicle from a second acceleration sensor of the at least two acceleration sensors. The method also includes deriving, with the electronic processor, an approximate yaw acceleration at the centerline of the vehicle based on the first acceleration value and the second acceleration value. The method also includes comparing, with the electronic processor, the approximate yaw acceleration to a threshold and initiating, with the electronic processor, one or more actions in response to the yaw acceleration exceeding the threshold.

Abstract: An information processor includes a route evaluation unit, a route selection unit, and a course creation unit. The route evaluation unit calculates route evaluation points for each of proposed routes in each of segments, on the basis of a condition of a road in the relevant one of the proposed routes. The segments are coupled between respective two nearest neighbors of a sequence from a starting point to a destination point through one or more via-points. The route selection unit selects, on the basis of the route evaluation points, one proposed route from the proposed routes for each of the segments. The course creation unit connects the proposed routes selected by the route selection unit, to create a course from the starting point to the destination point.