X Development LLC

Johan Ulrich Lewin Jessen

Anthony Sean Jules

Martin F Schubert

Matthew David Day

Michael Patrick Bauerly

Preeti Murali Talwai

Michael Jason Grundmann

Benjamin M Davis

Kristina Liv Larsen

Rowan M Ogden

Philip Edwin Watson

Matthew Sibigtroth

Phillip Edwin Watson

The subject matter of this specification generally relates to modular vehicles including separable pod and base units. In some implementations, a computing system installed in a vehicle base identifies a vehicle pod that is detachably connected to a chassis on the vehicle base. In response to identifying that the vehicle pod is detachably connected to the chassis on the vehicle base, a communications link can be established between the computing system installed in the vehicle base and a computing system installed in the vehicle pod. Based on information obtained through the communications link, the computing system installed in the vehicle base can determine a particular configuration of the vehicle pod that is detachably connected to the chassis. The computing system can then verify that the vehicle base can safely transport the vehicle pod while the vehicle pod is detachably connected.

Modular vehicles with detachable pods

A computing system may obtain, for each vehicle of a plurality of vehicles located within a location area, navigation data that indicates a travel route for the vehicle. Based on the navigation data for the plurality of vehicles, the computing system determines a subset of the plurality of vehicles that are within a threshold distance of each other and have respective travel routes that at least partially overlap. The computing system selects, based on a set of selection parameters, two or more vehicles among the subset of vehicles to form a platoon of vehicles that travel in a coordinated arrangement in proximity to each other during at least a portion of the respective travel routes of the selected vehicles. The computing system can direct the selected vehicles to form the platoon of vehicles.

Smart platooning of vehicles

A method of providing decisions to user queries includes: receiving, by at least one processor, a query transmitted from a client device; identifying, from a query database, a first query model; applying, by the at least one processor, the identified first query model to multiple user experience data entries from a user experience database, to obtain at least one correlation resulting from the application of the first query model to the multiple user experience data entries; and identifying, by the at least one processor, an answer to the query from the at least one correlation.

Personalized decision engine

A bone conduction device includes: an enclosure; and an adhesive applied to a surface of the enclosure, in which the enclosure includes: a bone conduction transducer configured to cause the enclosure to vibrate; at least one sensor configured to sense a non-audible input from a region of the user's skin to which the adhesive adheres and produce a sensor output signal in response to sensing the non-audible input, the sensor output signal being indicative of a current state of the user; and a transceiver coupled to the bone conduction transducer and to the at least one sensor, in which the transceiver is configured to a) receive the output signal from the sensor and transmit the output signal to a remote processor and b) in response to transmitting the output signal, receive the bone-conduction control signal from the remote processor and transmit the bone-conduction control signal to the bone conduction transducer.

Bone conduction speaker patch

This specification describes technologies for mental state measurement using sensor data obtained from sensors attached to objects. One embodiment is a method that includes receiving sensor data from sensors attached to non-wearable objects. The first and second attachable sensors each include an output and a sensor. The method further includes determining mental state data from the sensor data; and causing to be displayed a representation of a mental state based on the mental state data. The method can further include: deriving an action metric from the mental state data; comparing the action metric to a threshold; automatically taking an action when the action metric exceeds the threshold; collecting post action sensor data; determining post action mental state data based at least in part on the post action sensor data; and forwarding the post action mental state data for display of a representation of a mental state.

Mental state measurement using sensors attached to non-wearable objects

A method includes: receiving, at a processor that is remote from a bone conduction device adhered to a user's skin, a first output signal from the bone conduction device, the first output signal having been generated by a first sensor in the bone conduction device, the first sensor being configured to detect non-audible inputs; identifying, at the processor, a first measurement signal characteristic based on the first output signal; determining, at the processor, that the first measurement signal characteristic is indicative of a state of the user; selecting a control signal configured to cause a transducer in the bone conduction device to generate an output to alter the state of the user or the user's perception of the state; and transmitting the control signal from the processor to the bone conduction device.

Methods, apparatus, systems, and computer-readable media are provided for determining, based on a task to be performed by a robot and past behavior by robots while performing tasks similar to the task, a suggested task-level movement parameter for application to movement of the robot while performing the task; providing output indicative of the suggested task-level movement parameter; receiving input indicative of user selection of the suggested task-level movement parameter or a user-defined task-level movement parameter; determining, based on the received input, an actual task-level movement parameter to be applied to movement of the robot while performing the task; and identifying, based on the actual task-level movement parameter, a plurality of component-level movement parameters to be applied to a plurality of motion primitives implemented by one or more operational components of the robot to perform the task.

Suggesting, selecting, and applying task-level movement parameters to implementation of robot motion primitives

Methods and apparatus that adapt programming and/or control of a robot. The robot has at least one attachment area that can removably couple with any one of a plurality of end effectors. The programming and/or control is adapted based on received parameters of an end effector attached (or to be attached) to the attachment area of the robot. Some implementations are directed to adapting graphical user interface output of a robot programming application based on one or more parameters of an end effector for a robot being programmed via the robot programming application. Some implementations are directed to adapting control of a robot based on one or more parameters of an end effector attached (or to be attached) to the robot.

Adapting programming of a robot and/or control of the robot based on one or more parameters of an end effector of the robot

Methods, apparatus, systems, and computer-readable media are provided for training a path of a robot by physically moving the robot, wherein the particular trained path and/or particular robot component movements to achieve the trained path are dependent on which of a plurality of available user interface inputs are selected for the training. The trained path defines a path to be traversed by a reference point of the robot, such as a path to be traversed by a reference point of an end effector of the robot. The particular robot component movements to achieve the trained path include, for example, the orientations of various robot components at each of a plurality of positions along the path, the velocity of various components at each of a plurality of positions along the path, etc.

Generating a trained robot path based on physical manipulation of the robot and based on training user interface input(s) associated with the physical manipulation

Methods, apparatus, systems, and computer-readable media are provided for visually debugging robotic processes. In various implementations, a graphical user interface may be rendered that includes a flowchart representing a robotic process. A plurality of different logical paths through the robotic process may be represented by a plurality of different visible paths through the flowchart. In various implementations, robot operation data indicative of one or more implementations of the robotic process may be determined. Based on the robot operation data, a first logical path through the robotic process that satisfies a criterion may be identified. In various implementations, a first visual path through the flowchart may be selected that corresponds to the identified first logical path. In various implementations, the first visible path through the flowchart may be visually distinguished from a second visible path through the flowchart.

Visually debugging robotic processes

Methods, apparatus, systems, and computer-readable media are provided for training a path of a robot within a graphical user interface (GUI) and/or by physically moving the robot. In particular, the technology generates a trained path for the robot based on waypoints defined by a user and generates one or more parameters for one or more movement characteristics of the robot along the trained path. The parameters for the movement characteristics are generated based on spatial proximity of a plurality of the waypoints that are defined by the user.

Growing community of inventors

Mountain View, CA, United States of America

Johan Ulrich Lewin Jessen