10 results about "Vision based systems" patented technology

A trailer backup assist system and method are disclosed that utilize a steer-by-wire architecture and advanced control algorithms to enable intuitive and stable trailer reversing. A hitch angle determination module measures or estimates the angular relationship between a towing vehicle and a trailer. A proportional controller computes a desired hitch angle rate based on the difference between a target and current hitch angle, and a processing unit converts this rate to a front wheel steering angle using a linearized kinematic model. The system includes a trailer length estimator that passively infers trailer geometry during motion, and optionally applies torque feedback to the steering wheel to guide the driver. Sensor fusion from inertial sensors, mechanical linkages, or vision-based systems enables flexible hitch angle estimation. Experimental results demonstrate that the system stabilizes trailer motion with reduced driver input and prevents jackknifing through adaptive control.

A computer implemented method including: capturing, with a first image sensor of a camera that is disposed on an implement, a first sequence of images while the implement travels through an agricultural field; capturing, with a second image sensor of the camera, a second sequence of images while the implement travels through the agricultural field; training a neural network (NN) model with image data from at least one channel of the first image sensor and one channel of the second image sensor; and providing weed size as NN training target output channel.

The present invention relates to a vision-based system and method for relative positioning with respect to a target surface, characterised in that it comprises: at least three reference markers (1) located on the target surface on the vertices of an equilateral triangle (2) seen from an overhead view of said target surface; at least one image forming device located on the object; processing means configured to receive and process the captured images (4) and configured to either detect the reference markers (1) in the received image (4), or identify the centroid (5) of a triangle (7) formed by the reference markers (1) in the received image (4), or circumscribe the reference markers (1) by means of a circumscribed ellipse (6), or determine the relative position with respect to the target surface by means of the relationship between the circumscribed ellipse (6) and the position of the reference markers (1).

Aspects of the present application correspond to utilization of a combined set of inputs from simulation systems to generate or train machine learned algorithms for utilization in vehicles with vision system-only based processing. Aspects of the present application correspond to utilization of a set of inputs from sensors or sensing systems and simulation systems to create updated training sets for use in machine learning algorithms. The combined set of inputs includes a first set of data corresponding to vision system from a plurality of cameras configured in a vehicle. The combined set of inputs further includes a second set of data corresponding to simulated content systems that generate additional training set data including visual images and data labels to supplement the vision system data.

A system and method determines from data collected by one or more data collection elements of a computing device a plurality of discrete product storage locations within a product storage system. Each of the plurality of plurality of discrete product storage locations is caused to be associated with at least one cell of a grid comprised of a plurality of cells. A graphical user interface is displayed in a display of the computing device, the graphical user interface including the grid overlayed upon an image of the product storage system. A user may then interact with the graphical user interface to select a one or more of the plurality of cells of the grid and cause product related information captured via use of the one more data collection elements of the computing device to be linked in a memory storage associated with the computing device to the one of the plurality of discrete product storage locations that was associated with the selected at least one cell of the grid.

A vison-based system and method for assessing a condition of a component of a material handling vehicle and monitoring the use of personal protective equipment (PPE) and vehicle charging by operators are provided. The vison-based system includes one or more cameras of a perception system. The perception system can be configured to receive or otherwise retrieve input data from the one or more cameras and process the input data using a machine learning system. The system can identify the condition of the component(s) of the material handling vehicle, categorize the identified condition based on the output of the machine learning system, classify a severity of the condition, and generate a notification.

An Automated Computer-Vision based system and method for identifying potential hazards to building occupants in building exit pathways is described to address the inherent challenges in manual building safety inspections. The computer vision-based approach automates the inspection of an interior building hallway (exit access) for an obstruction that may be a potential hazard. The invention mitigates the risk of a hazard to the building occupants by sensing and alerting the safety officer before a situation turns into an emergency. Test results demonstrate that the Dual Temporal Buffer Differencing (DTBD) method of the invention can detect a potential hazard in the building exit access effectively and continuously. As a result, the invention can facilitate safety in the building and allow safety inspectors to make better use of resources.

Exemplary embodiments are disclosed of vision-based systems and methods for locomotive control and / or location determination. In exemplary embodiments, a system includes at least one camera positionable onboard a locomotive for capturing one or more images of trackside signage including location data corresponding with location(s) along a track. The system also includes at least one processor configured for communication with the at least one camera for receiving the one or more images of the trackside signage captured by the at least one camera. The at least one processor is configured to analyze the one or more images and visually recognize the location data of the trackside signage in the one or more images captured by the at least one camera, thereby enabling the system to identify the locomotive's location along the track via the at least one processor's visual recognition of the location data of the trackside signage.

Aspects of the present application correspond to utilization of a combined set of inputs from simulation systems to generate or train machine learned algorithms for utilization in vehicles with vision system-only based processing. Aspects of the present application correspond to utilization of a set of inputs from sensors or sensing systems and simulation systems to create updated training sets for use in machine learning algorithms. The combined set of inputs includes a first set of data corresponding to vision system from a plurality of cameras configured in a vehicle. The combined set of inputs further includes a second set of data corresponding to simulated content systems that generate additional training set data including visual images and data labels to supplement the vision system data.