Abstract: A method and system provide the ability to compile computer code. Human readable text in a programming language is optimized in a compiler, into a processor specific language. The optimization includes determining a set of two or more optimization routines, randomly selecting a selected optimization routine from the set of two or more optimization routines, and applying the selected optimization routine to each segment of the human readable text. Binary code is then output based on the optimized human readable text and has improved resistance to subversion.

Abstract: A service cart for an electric vehicle (EV) battery, comprising a lift assembly supporting a platform. The platform is configured to support the EV battery. The service cart comprises an electrically-driven hydraulic pump that is configured to extend and retract the lift assembly in order to raise and lower the platform. The service cart may comprise one or more electric wheels which may be driven by rotational force from a first electric motor, or controlled with respect to an adjustable directionality by a second electric motor.

Abstract: Disclosed herein are systems and methods for providing supplemental identification abilities to an autonomous vehicle system. The sensor unit of the vehicle may be configured to receive data indicating an environment of the vehicle, while the control system may be configured to operate the vehicle. The vehicle may also include a processing unit configured to analyze the data indicating the environment to determine at least one object having a detection confidence below a threshold. Based on the at least one object having a detection confidence below a threshold, the processor may communicate at least a subset of the data indicating the environment for further processing. The vehicle is also configured to receive an indication of an object confirmation of the subset of the data. Based on the object confirmation of the subset of the data, the processor may alter the control of the vehicle by the control system.

Abstract: Methods and systems for use of a reference image to detect a road obstacle are described. A computing device configured to control a vehicle, may be configured to receive, from an image-capture device, an image of a road on which the vehicle is travelling. The computing device may be configured to compare the image to a reference image; and identify a difference between the image and the reference image. Further, the computing device may be configured to determine a level of confidence for identification of the difference. Based on the difference and the level of confidence, the computing device may be configured to modify a control strategy associated with a driving behavior of the vehicle; and control the vehicle based on the modified control strategy.

Abstract: A method and system provide the ability to compile computer source code. The source code is pre-processed to generate pure source code that includes definitions required for interpretation. The pure source code is formalized in a compiler, into assembly language that is processor specific. The formalization includes determining a set of two or more optimization routines, randomly selecting a selected optimization routine from the set of two or more optimization routines, and applying the selected optimization routine to each segment of the pure source code in a serialized manner. An executable binary file is then output and executed based on the formalized pure source code.

Abstract: Disclosed herein are systems and methods for providing supplemental identification abilities to an autonomous vehicle system. The sensor unit of the vehicle may be configured to receive data indicating an environment of the vehicle, while the control system may be configured to operate the vehicle. The vehicle may also include a processing unit configured to analyze the data indicating the environment to determine at least one object having a detection confidence below a threshold. Based on the at least one object having a detection confidence below a threshold, the processor may communicate at least a subset of the data indicating the environment for further processing. The vehicle is also configured to receive an indication of an object confirmation of the subset of the data. Based on the object confirmation of the subset of the data, the processor may alter the control of the vehicle by the control system.

Abstract: Methods and systems for the use of detected objects for image processing are described. A computing device autonomously controlling a vehicle may receive images of the environment surrounding the vehicle from an image-capture device coupled to the vehicle. In order to process the images, the computing device may receive information indicating characteristics of objects in the images from one or more sources coupled to the vehicle. Examples of sources may include RADAR, LIDAR, a map, sensors, a global positioning system (GPS), or other cameras. The computing device may use the information indicating characteristics of the objects to process received images, including determining the approximate locations of objects within the images. Further, while processing the image, the computing device may use information from sources to determine portions of the image to focus upon that may allow the computing device to determine a control strategy based on portions of the image.

Abstract: A photovoltaic cell includes a semiconductor element (20) formed from a direct semiconductor and a transparent biasing agent (28) overlying a first portion of the front face (22) of the semiconductor, the biasing agent producing a first depletion region (30) in the semiconductor element. A collector (40) directly contacts a second portion of the front face. The collector produces a second depletion region (44) in the semiconductor element. The collector (40) is out of direct conductive contact with the biasing agent (28) but in proximity to the biasing agent. A continuous region at least partially depleted of majority carriers extends between the first and second depletion regions at the front face of the semiconductor element. The continuous region may include overlapping portions of the first and second depletion regions (30,44), or may include an additional depletion region (160) formed by a charged dielectric (147).

Abstract: Methods and systems for the use of detected objects for image processing are described. A computing device autonomously controlling a vehicle may receive images of the environment surrounding the vehicle from an image-capture device coupled to the vehicle. In order to process the images, the computing device may receive information indicating characteristics of objects in the images from one or more sources coupled to the vehicle. Examples of sources may include RADAR, LIDAR, a map, sensors, a global positioning system (GPS), or other cameras. The computing device may use the information indicating characteristics of the objects to process received images, including determining the approximate locations of objects within the images. Further, while processing the image, the computing device may use information from sources to determine portions of the image to focus upon that may allow the computing device to determine a control strategy based on portions of the image.

Abstract: Disclosed herein are systems and methods for providing supplemental identification abilities to an autonomous vehicle system. The sensor unit of the vehicle may be configured to receive data indicating an environment of the vehicle, while the control system may be configured to operate the vehicle. The vehicle may also include a processing unit configured to analyze the data indicating the environment to determine at least one object having a detection confidence below a threshold. Based on the at least one object having a detection confidence below a threshold, the processor may communicate at least a subset of the data indicating the environment for further processing. The vehicle is also configured to receive an indication of an object confirmation of the subset of the data. Based on the object confirmation of the subset of the data, the processor may alter the control of the vehicle by the control system.

Abstract: Disclosed herein are systems and methods for providing supplemental identification abilities to an autonomous vehicle system. The sensor unit of the vehicle may be configured to receive data indicating an environment of the vehicle, while the control system may be configured to operate the vehicle. The vehicle may also include a processing unit configured to analyze the data indicating the environment to determine at least one object having a detection confidence below a threshold. Based on the at least one object having a detection confidence below a threshold, the processor may communicate at least a subset of the data indicating the environment for further processing. The vehicle is also configured to receive an indication of an object confirmation of the subset of the data. Based on the object confirmation of the subset of the data, the processor may alter the control of the vehicle by the control system.

Abstract: A method and system provide the ability to compile computer source code. The source code is pre-processed to generate pure source code that includes definitions required for interpretation. The pure source code is formalized in a compiler, into assembly language that is processor specific. The formalization includes determining a set of two or more optimization routines, randomly selecting a selected optimization routine from the set of two or more optimization routines, and applying the selected optimization routine to each segment of the pure source code in a serialized manner. An executable binary file is then output and executed based on the formalized pure source code.

Abstract: According to one aspect, a method includes obtaining a request for a first vehicle from a customer, and dispatching the first vehicle to a first location identified in the request. Dispatching the first vehicle to the first location includes causing the first vehicle to drive in an autonomous mode. The method also includes determining when the first vehicle arrives at the first location, and providing the customer with access to enter the first vehicle.

Abstract: A photovoltaic cell includes a semiconductor element (20) formed from a direct semiconductor and a transparent biasing agent (28) overlying a first portion of the front face (22) of the semiconductor, the biasing agent producing a first depletion region (30) in the semiconductor element. A collector (40) directly contacts a second portion of the front face. The collector produces a second depletion region (44) in the semiconductor element. The collector (40) is out of direct conductive contact with the biasing agent (28) but in proximity to the biasing agent. A continuous region at least partially depleted of majority carriers extends between the first and second depletion regions at the front face of the semiconductor element, The continuous region may include overlapping portions of the first and second depletion regions (30,44), or may include an additional depletion region (160) formed by a charged dielectric (147).

Abstract: An autonomous vehicle is operated using a main autonomy system that analyzes data collected by a sensor system of the autonomous vehicle to determine a trajectory of travel of the autonomous vehicle, and wherein the main autonomy system provides instructions to a propulsion system of the autonomous vehicle to cause the propulsion system to navigate the autonomous vehicle according to the trajectory. In response to determining that navigating the autonomous vehicle according to the trajectory is likely to result in collision, instructions are provided from a parallel autonomy system to the propulsion system to cause the autonomous vehicle to avoid collision. In response to detecting a fault in the main autonomy system, control of the propulsion system is provided from the main autonomy system to a failover autonomy system, wherein the failover autonomy system is configured to override the propulsion system.

Abstract: According to some aspects, an additive fabrication device is provided configured to form layers of material on a build platform, each layer of material being formed so as to contact a container in addition to the build platform and/or a previously formed layer of material. The additive fabrication device may comprise a container and a wiper, wherein the wiper comprises a wiper arm and a wiper blade coupled to said wiper arm using a pivoting coupling.

Abstract: Methods and systems for the use of detected objects for image processing are described. A computing device autonomously controlling a vehicle may receive images of the environment surrounding the vehicle from an image-capture device coupled to the vehicle. In order to process the images, the computing device may receive information indicating characteristics of objects in the images from one or more sources coupled to the vehicle. Examples of sources may include RADAR, LIDAR, a map, sensors, a global positioning system (GPS), or other cameras. The computing device may use the information indicating characteristics of the objects to process received images, including determining the approximate locations of objects within the images. Further, while processing the image, the computing device may use information from sources to determine portions of the image to focus upon that may allow the computing device to determine a control strategy based on portions of the image.

Abstract: Disclosed herein are systems for navigating an autonomous or semi-autonomous fleet comprising a plurality of autonomous or semi-autonomous vehicles within a plurality of navigable pathways within an unstructured open environment.

Abstract: Methods and systems for use of a reference image to detect a road obstacle are described. A computing device configured to control a vehicle, may be configured to receive, from an image-capture device, an image of a road on which the vehicle is travelling. The computing device may be configured to compare the image to a reference image; and identify a difference between the image and the reference image. Further, the computing device may be configured to determine a level of confidence for identification of the difference. Based on the difference and the level of confidence, the computing device may be configured to modify a control strategy associated with a driving behavior of the vehicle; and control the vehicle based on the modified control strategy.