# US 2026/0227541 A1 · Autonomous Rover for Detection of Precious Metals and Meteorites > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2026/0227541 A1 - Document ID: US20260227541A1 - Status: Published application - Kind: A1 - Application number: 18/813,413 - Filed: 2024-08-23 - Published: 2026-08-06 - Earliest claimed: 2023-08-31 - Assignees: Craig Flanagan - Inventors: CRAIG Thomas FLANAGAN - Web page: https://patentgrep.com/patent/US20260227541A1 ## CPC - G01V 3/15: specially adapted for use during transport, e.g. by a person, vehicle or boat - G01V 3/38: Processing data, e.g. for analysis, for interpretation, for correction - G05D 1/648: Performing a task within a working area or space, e.g. cleaning - G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES ## Abstract Described herein is a rover-based method and system for finding gold nuggets, meteorites and other minerals detectable by electronic-based means. The rover runs autonomously after being provided with a waypoint mission by the operator. The autonomy of movement includes obstacle detection and avoidance. Target mineral detection is accomplished by means of a trained convolutional neural network which interprets audible and/or electronic signals from an integral metal detector. Missions run by the rover include, but are not limited to, detection of gold nuggets and meteorites. ## Claims ### Claim 1 A rover for use in the detection and location of gold or other valuable minerals, comprising: a vehicle; a metal detecting apparatus; a means of self-navigation. ### Claim 2 (depends on 1) The rover of claim 1, wherein the assessment of the presence of a valuable mineral species is performed by an integral artificial intelligence (AI) processor running AI code to interpret the electronic or audible sounds from an integral metal detector to provide a probabilistic assessment of the presence of the mineral species. ### Claim 3 (depends on 1) The rover of claim 1, wherein the assessment of the presence of a valuable mineral is performed using a two tiered process in which; first, a possible signal of the presence of a mineral is obtained while the rover is in forward motion, and second and upon receipt of the signal, the rover performs a confirmatory test of the presence of the mineral target. ### Claim 4 (depends on 1) The rover of claim 1, wherein two missions are preprogrammed into the rover, the first mission consisting of a prospecting mission to locate and record the GPS location of mineral targets, and a second mission to walk or direct the operator to the location of the targets. ### Claim 5 (depends on 1) The rover of claim 1, wherein a probabilistic threshold for the AI classification process is available for user setting. ### Claim 6 (depends on 1) The rover of claim 1, wherein multiple rovers may be deployed concurrently from a remote base station. ### Claim 7 (depends on 1) The rover of claim 1, wherein the navigational input from multiple sensors may be integrated in computer code into a single navigational signal. ### Claim 8 (depends on 1) The rover of claim 1, wherein Ackermann-type steering and speed control signals from the autopilot are converted by integral computer code into the steering and speed control requirements of the particular rover configuration employed. ### Claim 9 (depends on 1) The rover of claim 1, wherein the detection of valuable minerals is mediated by an AI algorithm consisting of a convolutional neural network (CNN) trained to assess, categorize and determine the probability of both the characteristics and existence of potential targets. ### Claim 10 (depends on 1) The rover of claim 1, wherein a phase-based averaging scheme based on sweeper movement is implemented for improved signal-to-noise ratio of the original signal. ### Claim 11 A means of determining the presence of valuable minerals consisting of: an artificial intelligence (AI) based algorithm to assess electronic and/or audible output from a metal detector; a self-navigating rover to carry said metal detector and said AI-based processing algorithm. ### Claim 12 (depends on 11) The means of claim 11, further comprising a two tiered process in which; first, a possible signal of the presence of a mineral target is obtained while the rover is in forward motion, and second and upon receipt of the signal, the rover performs a confirmatory test of the presence of the mineral target. ### Claim 13 (depends on 11) The means of claim 11, further comprising two missions preprogrammed into the said rover, the first mission consisting of a mission to locate and record the GPS location of mineral targets, and a second mission to walk or direct the operator to the location of said mineral targets. ### Claim 14 (depends on 11) The means of claim 11, further comprising a probabilistic threshold for the AI classification process available for user setting. ### Claim 15 (depends on 11) The means of claim 11, further comprising a means of deploying multiple rovers concurrently from a remote base station. ### Claim 16 (depends on 11) The means of claim 11, wherein the navigational input from multiple sensors may be integrated in computer code into a single navigational signal. ### Claim 17 (depends on 11) The means of claim 11, further comprising the detection of valuable minerals as mediated by an AI algorithm consisting of a convolutional neural network (CNN) trained to assess, categorize and determine the probability of both the characteristics and existence of potential targets. ### Claim 18 An algorithmic method for the determination of the presence of a valuable mineral consisting of: an AI-based platform to assess electronic and/or audible output of a metal detector; a two or more staged/tiered target evaluation process; one or more user defined probabilistic thresholds within said algorithmic method. ### Claim 19 (depends on 18) The method of claim 18, further comprising the detection of valuable minerals as mediated by an AI algorithm consisting of a convolutional neural network (CNN) trained to assess, categorize and determine the probability of both the characteristics and existence of potential targets. ### Claim 20 (depends on 18) The method of claim 18, further comprising a two or more tiered target evaluation method for the assessment of valuable mineral species in which, first, a possible signal of the presence of a mineral is obtained using a probabilistic threshold of an AI inferencing calculation, and second and upon receipt of said first confirmatory signal, a secondary or tiered evaluation of the presence of the mineral target is performed using a probabilistic threshold of an AI inferencing calculation.