Cybernet Systems Corporation

Other

Glenn J Beach

Charles J Jacobus

Charles J Cohen

Douglas Haanpaa

Steve Rowe

George V Paul

Gary Moody

James Burkowski

Eugene Foulk

Brook Cavell

Jay Obermark

Gene Foulk

Pritpaul Mahal

Amanda Christiana

Steven M Rowe

Gary Siebert

Joseph Long

Trevor Davey

Steven Rowe

An autonomous vehicle (an AV, or manual vehicle in an autonomous or semi-autonomous mode) includes the ability to sense a command from a source external to the vehicle and modify the behavior of the vehicle in accordance with the command. For example, the vehicle may visualize a police officer or other person associated with traffic control and interpret gestures made by the person causing the vehicle to stop, slow down, pull over, change lanes, back up or take a different route due to unplanned traffic patterns such as accidents, harsh weather, road closings or other situations. The system and method may also be used for non-emergency purposes, including external guidance for load pick-up/placement, hailing a vehicle used as a cab, and so forth. The command may further be spoken or may include a radio frequency (RF) light or other energy component.

Gesture recognition system for autonomous vehicle traffic control

Autonomous and manually operated vehicles are integrated into a cohesive, interactive environment, with communications to each other and to their surroundings, to improve traffic flow while reducing accidents and other incidents. All vehicles send/receive messages to/from each other, and from infrastructure devices, enabling the vehicles to determine their status, traffic conditions and infrastructure. The vehicles store and operate in accordance with a common set of rules based upon the messages received and other inputs from sensors, databases, and so forth, to avoid obstacles and collisions based upon current and, in some cases, future or predicted behavior. Shared vehicle control interfaces enable the AVs to conform to driving activities that are legal, safe, and allowable on roadways. Such activities enable each AV to drive within safety margins, speed limits, on allowed or legal driving lanes and through allowed turns, intersections, mergers, lane changes, stops/starts, and so forth.

Autonomous transportation system and methods

Autonomous vehicles are capable of executing missions that abide by on-street rules or regulations, while also being able to seamlessly transition to and from 'zones,' including off-street zones, with their our set(s) of rules or regulations. An on-board memory stores roadgraph information. An on-board computer is operative to execute commanded driving missions using the roadgraph information, including missions with one or more zones, each zone being defined by a sub-roadgraph with its own set of zone-specific driving rules and parameters. A mission may be coordinated with one or more payload operations, including zone with “free drive paths” as in a warehouse facility with loading and unloading zones to pick up payloads and place them down, or zone staging or entry points to one or more points of payload acquisition or placement. The vehicle may be a warehousing vehicle such as a forklift.

Autonomous vehicles and methods of zone driving

An in-vehicle system for generating precise, lane-level road map data includes a GPS receiver operative to acquire positional information associated with a track along a road path. An inertial sensor provides time local measurement of acceleration and turn rate along the track, and a camera acquires image data of the road path along the track. A processor is operative to receive the local measurement from the inertial sensor and image data from the camera over time in conjunction with multiple tracks along the road path, and improve the accuracy of the GPS receiver through curve fitting. One or all of the GPS receiver, inertial sensor and camera are disposed in a smartphone. The road map data may be uploaded to a central data repository for post processing when the vehicle passes through a WiFi cloud to generate the precise road map data, which may include data collected from multiple drivers.

System and method for generating precise road lane map data

A fully automated, integrated, end-to-end synchronized and compact manufacturing system produces polymer or metal case ammunition. Manufacturing stations support case assembly, sealing (gluing/welding), final product inspection, cartridge packaging or binning, and loading. Station modularity facilitates rapid changeover to accommodate ammunition of differing calibers. Sensors and apparatus may be provided to place a manufacturing cell in a wait state until all components or materials are received in a preferred orientation for proper assembly. The system may join and use multipart cases, each including a lower portion with a head end attached thereto and at least one upper portion having a necked-down transition to the open top end. Elevator feeders, vibratory bowl feeders, and robotic pick-and-place feeders may be used to deliver components for assembly.

Integrated polymer and metal case ammunition manufacturing system and method

Automated inventory management and material (or container) handling removes the requirement to operate fully automatically or all-manual using conventional task dedicated vertical storage and retrieval (S&R) machines. Inventory requests Automated vehicles plan their own movements to execute missions over a container yard, warehouse aisles or roadways, sharing this space with manually driven trucks. Automated units drive to planned speed limits, manage their loads (stability control), stop, go, and merge at intersections according human driving rules, use on-board sensors to identify static and dynamic obstacles, and human traffic, and either avoid them or stop until potential collision risk is removed. They identify, localize, and either pick-up loads (pallets, container, etc.) or drop them at the correctly demined locations. Systems without full automation can also implement partially automated operations (for instance load pick-up and drop), and can assure inherently safe manually operated vehicles (i.e., trucks that do not allow collisions).

Automated warehousing using robotic forklifts or other material handling vehicles

A machine vision system for automatically identifying and inspecting objects is disclosed, including composable vision-based recognition modules and a decision algorithm to perform the final determination on object type and quality. This vision system has been used to develop a Projectile Identification System and an Automated Tactical Ammunition Classification System. The technology can be used to create numerous other inspection and automated identification systems.

Object inspection and sorting system

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Brooklyn, MI, United States of America

Glenn J Beach