US 12,649,240 B1

A computer-implemented artificial intelligence (AI) software control system for autonomously performing adaptive vehicle lighting installation and servicing, the system comprising:

a.a sensing module configured to generate a three-dimensional digital model of a vehicle's interior and/or exterior surfaces and structures at diverse operational locations, including fixed facilities and mobile or on-site customer premises;

b.an AI control module configured to:

b.i.process said three-dimensional digital model to generate an installation and/or servicing plan for lighting components based on a desired lighting pattern or a diagnostic or repair task, said processing including dynamically adapting to environmental conditions of said operational locations, said adaptation including compensation for variable ambient lighting, temperature fluctuations, and ground irregularities;

b.ii.learn and adapt robotic manipulation sequences for delicate tasks from expert demonstrations or operational feedback, said learning including the utilization of synthetically generated high-fidelity training data via generative AI and a closed-loop feedback mechanism for continuous model refinement; and

b.iii.generate real-time control commands, said commands adapting to real-time sensor feedback and environmental variations encountered at said operational locations; and

c.a controller operatively coupled to one or more robotic actuators configured to control at least one robotic platform to:

c.i.execute said installation and/or servicing plan by manipulating said vehicle and said lighting components;

c.ii.perform precision placement, repair, or replacement of said lighting components using specialized end-effectors with integrated active sensing and controlled force application, said force application maintaining material integrity for delicate vehicle components associated with headliner fabric, plastic trim, or wiring harnesses; and

c.iii.respond to said real-time control commands from said AI control module.

The system of claim 1, wherein the at least one robotic platform includes a humanoid robot, a gantry robot, and/or a mobile robot, configured for operation in both fixed and mobile deployment scenarios.

The system of claim 1, wherein the AI control module's learning and adaptation includes machine learning, natural language processing, generative AI including high-fidelity synthetic data generation, imitation learning, and reinforcement learning.

The system of claim 1, wherein the controller is configured to control the at least one robotic platform to autonomously select and operate a variety of interchangeable end-effectors, including at least one of: adhesive applicators, fastening devices, fiber optic manipulators, trim removal tools, wiring tools, or polishing or buffing tools for lens restoration, said selection enabled by a modular change mechanism with automated tool management and maintenance.

The system of claim 1, further comprising integrated sensors on the at least one robotic platform configured to monitor lighting component placement, tension, LED alignment, beam pattern, and wiring integrity during installation and servicing, and to enable real-time quality assurance and corrective actions, said quality assurance data feeding back into the AI control module for continuous learning and predictive maintenance insights.

The system of claim 1, wherein the AI control module is configured to operate autonomously without continuous internet connectivity through the use of on-device AI models, enabling robust mobile and on-site deployments.

The system of claim 1, further comprising a user interface for remote monitoring, lighting customization, and supervisory control with human override capability, said user interface supporting intuitive control, detailed error handling, and customization workflow, wherein a user can select a specific aesthetic lighting pattern from said user interface, prompting the AI control module to generate a corresponding robotic installation plan incorporating unique placement and wiring sequences, said system further configured to wirelessly synchronize the installed or serviced lighting with vehicle infotainment and ambient control systems, and allow remote oversight of operations at mobile or on-site locations.

The system of claim 1, further comprising an intelligent power management system for mobile deployments, configured to optimize energy consumption and utilize auxiliary power sources for sustained operation.

The system of claim 1, wherein the robotic platform and its components are designed for environmental robustness, including resistance to temperature extremes, moisture, dust, and wind, for reliable outdoor and mobile operations.

The system of claim 1, further comprising a fleet management system for centralized monitoring, software updates, diagnostic reporting, and task assignment across multiple deployed robotic units, wherein said fleet management system enables over-the-air deployment of updated AI models and software patches to a plurality of robotic units, facilitating rapid integration of new vehicle models and lighting patterns.

The system of claim 1, further comprising a data security and privacy module configured to secure sensitive vehicle data, ensure data privacy during on-site operations, and protect the integrity of AI models by performing real-time anonymization of personally identifiable information (PII) within scanned data and encrypting all data transmissions and storage.

A computer-implemented method for autonomously performing adaptive vehicle lighting installation and servicing using at least one robotic platform, the method comprising:

a.obtaining a three-dimensional digital model of a vehicle's interior and/or exterior surfaces and structures using a vision system, said obtaining occurring at diverse operational locations, including fixed facilities and mobile or on-site customer premises, said vision system dynamically compensating for variable ambient lighting conditions;

b.processing said three-dimensional digital model via an AI control system to generate an installation and/or servicing plan for lighting components based on a desired lighting pattern or a diagnostic or repair task, said processing including dynamically adapting to environmental conditions of said operational locations;

c.instructing said at least one robotic platform, via said AI control system, to autonomously transport itself and/or its associated mobile service unit to a specified vehicle location and manipulate and prepare said vehicle for lighting installation and/or servicing, including dynamically adapting its posture or position to access installation areas regardless of environmental constraints, and managing power supply from integrated or auxiliary sources for sustained operation;

d.instructing said at least one robotic platform to autonomously install, repair, or replace said lighting components into said vehicle according to said installation and/or servicing plan, utilizing precision robotic manipulation and tactile feedback from specialized end-effectors with integrated active sensing, said specialized end-effectors being autonomously selected and maintained via a change and automated tool management mechanism;

e.instructing said at least one robotic platform to autonomously route and connect associated wiring for said lighting components, and to interface with vehicle diagnostic systems for functional verification; and

f.performing real-time quality control and corrective adjustments of said installation and/or servicing using robot-integrated sensors and said AI control system, said quality control findings automatically updating machine learning models for continuous improvement, thereby enabling completion of services within six hours or same-day completion through multi-robot or human-robot collaboration, with integrated error handling and remote troubleshooting capabilities, including autonomous recovery from unexpected obstructions or minor tool malfunctions.

The method of claim 12, wherein the at least one robotic platform includes a humanoid robot, a gantry robot, and/or a mobile robot, configured for operation in both fixed and mobile deployment scenarios.

The method of claim 12, wherein obtaining said three-dimensional digital model includes scanning a vehicle interior roof for starlight installation, a vehicle underbody for underglow installation, and/or vehicle front or rear fascias for functional lighting servicing, said scanning occurring in a fixed facility or at an on-site customer location, with dynamic lighting compensation.

The method of claim 12, wherein installing, repairing, or replacing said lighting components includes performing precision insertion of fiber optic strands into a headliner, securely attaching LED strips to vehicle underbody structures, and/or precise removal, replacement, or restoration of headlight or taillight assemblies, with the robotic platform dynamically adapting to real-time environmental feedback and utilizing comprehensive vehicle-specific data.