Storage and retrieval system case unit detection
US-9517885-B2 · Dec 13, 2016 · US
US2026030901A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2026030901-A1 |
| Application number | US-202418786781-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jul 29, 2024 |
| Priority date | Jul 29, 2024 |
| Publication date | Jan 29, 2026 |
| Grant date | — |
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A system for automatically identifying available docking positions using a vision system of a marine vessel is provided, the system comprising: an imaging device, wherein the imaging device is configured to be mounted to the marine vessel with an associated field of view of an environment of the marine vessel; and one or more hardware processors configured to: identify, based on image data captured using the imaging device, a dock instance; determine, based on the image data, whether the dock instance is available for docking; indicate that the dock instance is an available docking position; and cause the marine vessel to maneuver to the available docking position.
Opening claim text (preview).
What is claimed is: 1 . A system for automatically identifying available docking positions using a vision system of a marine vessel, the system comprising: an imaging device, wherein the imaging device is configured to be mounted to the marine vessel with an associated field of view of an environment of the marine vessel; and one or more hardware processors configured to: identify, based on image data captured using the imaging device, a dock instance; determine, based on the image data, whether the dock instance is available for docking; indicate that the dock instance is an available docking position; and cause the marine vessel to maneuver to the available docking position. 2 . The system of claim 1 , wherein the imaging device comprises a stereoscopic camera. 3 . The system of claim 1 , wherein the one or more hardware processors are further configured to: provide the image data to a trained object detection model, wherein the trained object detection model is trained to identify instances of objects in input image data corresponding to a plurality of classes, including a dock class; receive, from the trained object detection model, object detection information indicative of a location and size of the dock instance; and identify the dock instance based on the object detection information. 4 . The system of claim 1 , wherein the one or more hardware processors are further configured to: provide the image data to a trained image segmentation model, wherein the trained image segmentation model is trained to classify each portion of input image data as corresponding to a class of a plurality of classes, including a dock class; receive, from the trained image segmentation model, segmentation information indicative of a location and size of the dock instance; and identify the instance dock based on the segmentation information. 5 . The system of claim 1 , wherein the one or more hardware processors are further configured to: identify, based on the image data captured using the imaging device, a second dock instance; determine whether a dock bounding box associated with the dock instance overlaps one or more non-dock bounding boxes associated with one or more non-dock objects by at least a threshold amount; and in response to determining that the dock bounding box overlaps one or more non-dock bounding boxes by at least the threshold amount, determine that the second dock instance is not available for docking. 6 . The system of claim 1 , wherein the one or more hardware processors are further configured to: determine whether an amount of open water near the dock instance is sufficient for docking the marine vessel; and in response to determining that the amount of open water near the dock instance is sufficient for docking the marine vessel, determine that the dock instance is available for docking. 7 . The system of claim 6 , wherein the one or more hardware processors are further configured to: identify a portion of image data within a dock bounding box associated with the dock instance classified as water in segmentation information; determine whether the portion classified as water exceeds a threshold portion of the dock bounding box; and in response to determining that the portion classified as water exceeds the threshold portion of the dock bounding box, determine that the amount of open water near the dock instance is sufficient for docking the marine vessel. 8 . The system of claim 1 , wherein the one or more hardware processors are further configured to: label a portion of a model of the marine environment adjacent to the dock instance as available for docking, wherein the portion of the model comprises a portion of the image data that is classified as water and within a dock bounding box associated with the dock instance; and indicate that the dock instance is an available docking position based on the labeled portion of the model. 9 . The system of claim 8 , wherein the model comprises an occupancy grid. 10 . The system of claim 8 , wherein the one or more hardware processors are further configured to: cause a graphical user interface to be presented that includes a user interface element that represents a location of the available docking position with respect to a portion of a dock in the environment that corresponds to the dock instance; receive, via the graphical user interface, input that causes the available docking position to be selected as a target docking position; and in response to receiving the input that causes the available docking position to be selected, cause the marine vessel to maneuver to the target docking position. 11 . The system of claim 1 , further comprising: a marine propulsion system comprising one or more propulsion devices, wherein the one or more hardware processors are further configured to: receive an indication that the available docking position has been selected as a target docking position; determine a path to the target docking position; determine marine vessel movements to cause the marine vessel to travel along the path; and output the marine vessel movements to the marine propulsion system, thereby causing the marine propulsion system to actuate the one or more propulsion devices to propel the marine vessel to the available docking location without further intervention from an operator of the marine vessel. 12 . A method for automatically identifying available docking positions using a vision method of a marine vessel, the method comprising: identifying, based on image data captured using an imaging device, a dock instance, wherein the imaging device is configured to be mounted to the marine vessel with an associated field of view of an environment of the marine vessel; determining, based on the image data, whether the dock instance is available for docking; indicating that the dock instance is an available docking position; and causing the marine vessel to maneuver to the available docking position. 13 . The method of claim 12 , wherein the imaging device comprises a stereoscopic camera. 14 . The method of claim 12 , further comprising providing the image data to a trained object detection model, wherein the trained object detection model is trained to identify instances of objects in input image data corresponding to a plurality of classes, including a dock class; receiving, from the trained object detection model, object detection information indicative of a location and size of the dock instance; and identifying the dock instance based on the object detection information. 15 . The method of claim 12 , further comprising providing the image data to a trained image segmentation model, wherein the trained image segmentation model is trained to classify each portion of input image data as corresponding to a class of a plurality of classes, including a dock class; receiving, from the trained image segmentation model, segmentation information indicative of a location and size of the dock instance; and identifying the instance dock based on the segmentation information. 16 . The method of claim 12 , further comprising identifying, based on the image data captured using the imaging device, a second dock instance; determining whether a dock bounding box associated with the dock instance overlaps one or more non-dock bounding boxes associated with one or more non-dock objects by at least a threshold amount; and in response to determining that the dock bounding box overlaps one or more non-dock bounding boxes by at least the threshold
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