Methods and apparatus for mobile additive manufacturing of advanced roadway systems
The present disclosure provides various aspects for mobile and automated processing utilizing additive manufacturing. The present disclosure includes methods processing vision system data. Vision system image data may be processed by artificial intelligence algorithms. The artificial intelligence algorithms may perform GAN based synthesis of image edits to plan deposits of sized features upon detected defects of a surface. An artificial intelligence chip may perform rapid image processing on the fly as a mobile additive manufacturing apparatus functions.
1 . A method for depositing materials upon a surface, the method comprising:
receiving a first image representation in a controller of an apparatus from a vision system of the apparatus, wherein the apparatus is a mobile additive manufacturing apparatus comprising:
a controller capable of executing algorithms and providing control signals,
an additive manufacturing system to deposit a line feature material at prescribed locations across a surface of a roadway according to a first digital model processed by the controller,
a drive system operative to transport the additive manufacturing system along the surface,
a vision system to receive images of the surface of the roadway,
a navigation system to determine a location of the mobile additive manufacturing system and guide the drive system, and
a power system capable of providing power to operate at least the drive system, navigation system, controller and additive manufacturing system;
recognizing a registration mark printed upon the surface, and comparing a size and a location of the registration mark to a model and modifying the first digital model to generate control signals for the additive manufacturing system of the additive manufacturing apparatus;
transmitting a control signal to the additive manufacturing system of the additive manufacturing apparatus,
adding a first material to the surface with the mobile additive manufacturing apparatus and wherein the first material is added to the surface in a first pattern;
moving the mobile additive manufacturing apparatus with the drive system to a new location;
confirming the location of the mobile additive manufacturing system with the navigation system; and
adding the first material to the surface in a second pattern according to the first digital model when the mobile additive manufacturing system is at the new location.
2 . The method of claim 1 further comprising analyzing the first image representation with an artificial intelligence algorithm, wherein the analyzing of the first image representation with the artificial intelligence algorithm extracts features and semantic segmentation aspects from the image.
3 . The method of claim 2 wherein the artificial intelligence algorithm has been trained to utilize images and associated feature and semantic segmentation extraction to perform a first editing of the first image representation to create a second image representation.
4 . The method of claim 3 wherein the artificial intelligence system has been trained to apply a predetermined edit to a feature type.
5 . The method of claim 4 wherein the predetermined edit of the feature type is used to create an editing vector which is imbedded into the latent space of the artificial algorithm.
6 . The method of claim 5 wherein the second image representation is created by running the artificial intelligence algorithm with the latent space resulting from applying the editing vectors.
7 . The method of claim 6 wherein the predetermined edit of the feature type performs at least a change of the feature's two dimensional size.
8 . The method of claim 6 wherein the predetermined edit of the feature type performs at least a change of the feature's two dimensional location.
9 . The method of claim 6 wherein the predetermined edit of the feature type performs at least a change of the feature's three dimensional height, wherein the image comprises a three dimensional representation of the surface.
10 . The method of claim 3 further comprising receiving a second image representation from the vision system of the mobile additive manufacturing apparatus, wherein the second image representation shows at least in part a view of the processed area of the surface.
11 . The method of claim 10 further comprising analyzing the second image representation with the artificial intelligence algorithm and comparing features in the second image representation with corresponding features in the first image representation to determine whether an adjustment of parameters of the editing vectors is required.
12 . A method for depositing materials upon a surface, the method comprising:
receiving a first image in a controller of an apparatus from a vision system of the apparatus, wherein the apparatus is a mobile additive manufacturing apparatus comprising:
a controller capable of executing algorithms and providing control signals,
an additive manufacturing system to deposit a line feature material at prescribed locations across a surface of a roadway according to a first digital model processed by the controller,
a drive system operative to transport the additive manufacturing system along the surface,
a vision system to receive images of the surface of the roadway,
a navigation system to determine a location of the mobile additive manufacturing system and guide the drive system, and
a power system capable of providing power to operate at least the drive system, navigation system, controller and additive manufacturing system;
analyzing the first image representation with an artificial intelligence algorithm, wherein the analyzing of the first image representation with the artificial intelligence algorithm extracts features and semantic segmentation aspects from the image;
transmitting a control signal to the additive manufacturing system of the additive manufacturing apparatus,
adding a first material to the surface with the mobile additive manufacturing apparatus and wherein the first material is added to the surface in a first pattern;
moving the mobile additive manufacturing apparatus with the drive system to a new location;
confirming the location of the mobile additive manufacturing system with the navigation system; and
adding the first material to the surface in a second pattern according to the first digital model when the mobile additive manufacturing system is at the new location.
13 . The method of claim 12 wherein the artificial intelligence algorithm has been trained to utilize images and associated feature and semantic segmentation extraction to perform a first editing of the first image representation to create a second image representation.
14 . The method of claim 13 wherein the artificial intelligence system has been trained to apply a predetermined edit to a feature type.
15 . The method of claim 14 wherein the predetermined edit of the feature type is used to create an editing vector which is imbedded into the latent space of the artificial algorithm.
16 . The method of claim 15 wherein the second image representation is created by running the artificial intelligence algorithm with the latent space resulting from applying the editing vectors.
17 . The method of claim 16 wherein the predetermined edit of the feature type performs at least a change of the feature's two dimensional size.
18 . The method of claim 16 wherein the predetermined edit of the feature type performs at least a change of the feature's two dimensional location.
19 . The method of claim 16 wherein the predetermined edit of the feature type performs at least a change of the feature's three dimensional height, wherein the image comprises a three dimensional representation of the surface.
20 . The method of claim 12 wherein the analyzing the first image representation with an artificial intelligence algorithm comprises at least in part utilizing an artificial intelligence chip to perform the artificial intelligence algorithm processing steps.