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EP-4513380-B1 - ROBOTIC DEVICES

EP4513380B1EP 4513380 B1EP4513380 B1EP 4513380B1EP-4513380-B1

Inventors

  • CRISTACHE, LUCIAN

Dates

Publication Date
20260513
Application Date
20200102

Claims (16)

  1. A semantic augmentation robotic system, comprising: a memory storing a plurality of stored semantic rules, the semantic rules comprising composition and management plans including one or more of timing, ratings, weightings, or access control; the memory further storing a plurality of endpoints and a plurality of semantic routes associated with the endpoints; at least one processor and a computer program operable by the at least one processor; the computer program being configured to use semantic factorization to apply a quantifiable factor or indicator which is inferred based on at least one of the stored semantic routes or semantic rules to cause the presentation of a first user interface object for display on a user interface; the presentation of the first user interface object for display on the user interface being further based on a semantic time; wherein the computer program is configured to infer the semantic time based on the inference of a first semantic at a first time and the inference of a second semantic at a second time, the inference of each of the first semantic and the second semantic being associated with one or more aspects of at least one of the semantic rules or the semantic routes; and wherein, based on the inference of the second semantic at the second time, the computer program is configured to invalidate the inference of the first semantic and cause the expiration of the semantic time.
  2. The semantic augmentation robotic system of claim 1, further being configured to infer a third semantic having semantic entropy or drift in rapport with the quantifiable factor or indicator, and wherein the presentation of the user interface object is in association with or based on the inferred third semantic.
  3. The semantic augmentation robotic system of claim 1, wherein the first user interface object is associated with a first endpoint among the plurality of endpoints.
  4. The semantic augmentation robotic system of claim 3, wherein the first user interface object is a user interface control.
  5. The semantic augmentation robotic system of claim 3, wherein the first user interface object is rendered in a user interface control associated with the first endpoint.
  6. The semantic augmentation robotic system of claim 3, wherein a second endpoint includes a plurality of endpoints, the plurality of endpoints including the first endpoint.
  7. The semantic augmentation robotic system of claim 1, wherein the system performs semantic gating based on semantic inferences related to at least one video frame.
  8. The semantic augmentation robotic system of claim 7, wherein the semantic augmentation robotic system performs image and video processing and further, wherein the semantic augmentation robotic system performs gating of video frames based on the semantic time.
  9. The semantic augmentation robotic system of claim 8, wherein the semantic augmentation robotic system performs semantic augmentation on video artifacts.
  10. The semantic augmentation robotic system of claim 1, wherein the semantic augmentation robotic system forms a semantic group comprising the first user interface object based on semantic resonance.
  11. The semantic augmentation robotic system of claim 1, wherein the semantic augmentation robotic system couples with a display based on ad-hoc semantic coupling to display the first user interface object.
  12. The semantic augmentation robotic system of claim 2, wherein the semantic augmentation robotic system redirects the semantic augmentation to a wireless device based on ad hoc semantic coupling.
  13. A semantic augmentation robotic method comprising: storing plurality of semantic routes and a plurality of semantic rules the semantic rules comprising composition and management plans including one or more of timing, ratings, weightings, or access control, the semantic routes being associated with a plurality of endpoints; applying semantic factorization to apply a quantifiable factor or indicator which is based on at least one of the stored semantic routes or semantic rules based on semantic inference or analysis associated with a semantic time; causing the display of a first user interface object based on the quantifiable factor or indicator, wherein the semantic time is inferred based on the inference of a first semantic at a first time; and inferring a second semantic at a second time, the inference of each of the first semantic and the second semantic being associated with one or more aspects of at least one of the semantic rules or the semantic routes, and further wherein the inference of the second semantic at the second time causing the invalidation of the inference of the first semantic and the expiration of the semantic time.
  14. The semantic augmentation robotic method of claim 13, further comprising inferring a third semantic having semantic entropy or drift in rapport with the quantifiable factor or indicator, and further wherein the displaying of the user interface object is based on or comprises the third semantic.
  15. The semantic augmentation robotic method of claim 13, further comprising inferring a third semantic having semantic entropy or drift in rapport with the first semantic or the second semantic, and further wherein the expiration of the semantic time is based on the inference of the third semantic.
  16. The semantic augmentation robotic method of claim 15, wherein the semantic augmentation is directed to a wireless device based on ad hoc semantic coupling.

Description

FIELD OF THE INVENTION This invention relates generally to robotic devices, including communicatively coupled devices which use variable semantic coherent inferences to allow the devices to perform semantic augmentation BACKGROUND OF THE INVENTION There are many cases in which physical devices are used in a variety of settings involving groups of people and/or objects, such as in the formation of posts and lines to demark crowd control areas or permitted pathways for movement. These provide regions which may be fluid, and tend to require manpower to continually reconfigure them. The posts themselves provide opportunities for gathering/inferring/presenting/rendering/conveying information which may be optical, visual, or otherwise. Robotic devices of this sort may serve a variety of purposes in both gathering/inferring/presenting/rendering/conveying information and demarking areas. WALCZAK KRZYSZTOF ET AL: "Building Contextual Augmented Reality 1 Environments with semantics", 2014 INTERNATIONAL CONFERENCE ON VIRTUAL SYSTEMS & MULTIMEDIA (VSMM), IEEE, 9 December 2014, pages 353-361, XP032790269 describes a new method of building contextual augmented reality environments through semantic tranformation of high-level domain ontologies. SUMMARY OF THE INVENTION The invention is defined in the appended claims. One example of the invention includes a semantic robotic system comprising a plurality of communicatively coupled devices which use a plurality of semantic routes and rules and variable semantic coherent inferences based on such routes and rules to allow the devices to perform semantic augmentation. In some versions, the devices comprise semantic posts. In some preferred versions, the devices comprise autonomous robotic carriers. In some examples of the invention, the devices comprise semantic composable modules. In preferred versions of the invention, the devices comprise semantic units. In some versions, the semantic system includes a semantic gate. In some examples, the semantic system comprises a semantic cyber unit. In a preferred implementation of the invention, the semantic posts implement crowd control. In one example, the semantic posts implement guiding lanes. In some examples, the semantic units perform signal conditioning. In some versions of the invention, the signal conditioning is based on semantic wave conditioning, preferably based on semantic gating. In some examples, the system performs video processing. In some examples of the invention, the system performs semantic augmentation on video artifacts. In preferred versions, the system may form semantic groups of posts and physically connect them through physical movement of the semantic posts motor components. Preferably, the system uses concern factors in order to determine coherent inferences. In some examples, the system forms a semantic group based on semantic resonance. Preferably, the system invalidates a semantic group based on semantic decoherence. In some examples, the system performs semantic learning based on the inference of semantic resonance. In some versions, the system performs semantic learning based on the inference of semantic decoherence. Preferably, the system learns semantic rules based on semantic resonance. In preferred versions, the system learns damping factor rules. Preferably, the system learns semantic gating rules. In some examples, the system learns a hysteresis factor based on semantic analysis. In preferred versions, the system performs semantic augmentation using a variety of augmentation modalities. In some examples, the system performs semantic augmentation comprising semantic displaying. Preferably, the system performs semantic augmentation on particular devices based on ad-hoc semantic coupling. In some examples, the system performs semantic augmentation based on challenges and/or inputs. In some examples, the system performs semantic encryption. In some examples, the system performs semantic gating based on semantic inferences related to at least one video frame. In preferred versions, the system uses semantic groups to form composite carriers. In some examples, the devices comprise semantic meshes. In some cases, the devices comprise biological sensors. In preferred examples, the biological sensors comprise at least one medical imaging sensor. BRIEF DESCRIPTION OF THE DRAWINGS Preferred and alternative examples of the present invention are described in detail below with reference to the following drawings: Fig. 1 is a front perspective view of a preferred smart post.Fig. 2A is a front perspective view of a preferred optical module with dome for a preferred smart post.Fig. 2B is a front perspective view of an alternate optical module for a preferred smart post.Figure 3 is a front perspective view of a preferred module with multi-array antenna elements for a preferred smart post.Fig. 4 is a front perspective view of a preferred clipping module for a preferred smart post.Fig. 5A is a front perspective view