# US 11,906,961 B2 · Systems and methods for unmanned vehicles having self-calibrating sensors and actuators > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,906,961 B2 - Document ID: US11906961B2 - Status: Granted - Kind: B2 - Application number: 17/220,111 - Filed: 2021-04-01 - Published: 2021-09-16 - Granted: 2024-02-20 - Earliest claimed: 2014-11-07 - Assignees: Clearpath Robotics Inc. - Applicants: Clearpath Robotics Inc. - Inventors: Ryan Christopher Gariepy; Kareem Shehata; Prasenjit Mukherjee; Anthony Tod; Teyvonia Thomas; Yan Ma - Web page: https://patentgrep.com/patent/US11906961B2 ## CPC - G05D 1/0011: {associated with a remote control arrangement} - G05D 1/024: {in combination with a laser (lasers per se H01S)} - G05D 1/0246: {using a video camera in combination with image processing means} - G05D 1/223: Command input arrangements on the remote controller, e.g. joysticks or touch screens - G05D 1/247: using signals provided by artificial sources external to the vehicle, e.g. navigation beacons - G05D 1/249: from positioning sensors located off-board the vehicle, e.g. from cameras - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES ## Abstract Systems and methods of unmanned vehicles having self-calibrating sensors and actuators are provided. The unmanned vehicle comprises a communication interface and a processor for controlling a propulsion system of the vehicle and receiving sensor data from one or more sensors of the vehicle. The processor is configured to operate in a guided calibration mode by controlling the propulsion system according to commands received from an external guided control system, while processing the sensor data to determine a degree of certainty on a calibration the sensor data and a position of the vehicle. The processor determines that the degree of certainty is above a threshold value associated with safe operation of the propulsion system in an autonomous calibration mode, and subsequently switch operation of the propulsion system to the autonomous calibration mode based on the determination that the degree of certainty is above the threshold value. ## Claims ### Claim 1 An unmanned vehicle comprising: a chassis; a processor for controlling a propulsion system of the unmanned vehicle and receiving sensor data from one or more sensors of the unmanned vehicle, the processor is configured to: prior to entering an autonomous calibration mode, enumerate unmanned vehicle capabilities, by one or more of: receiving a weight of the unmanned vehicle; receiving one or more dimensions of the unmanned vehicle; autodetecting each of the one or more sensors; receiving a list of the one or more sensors; and using a scanner to scan one or more graphical identifiers of the one or more sensors; operate the propulsion system in the autonomous calibration mode by: automatically controlling the propulsion system to move the chassis; collecting the sensor data from the one or more sensors; selecting one or more uncertainty propagation models from a plurality of uncertainty propagation models based on at least one of i.) one or more unmanned vehicle capabilities and ii.) the sensor data; and processing the sensor data using the one or more uncertainty propagation models to determine at least one degree of certainty on a calibration of one or more of the sensor data and a position of the chassis; determine that the degree of certainty is above a threshold value; and subsequently switch operation of the propulsion system to an operational mode based on the determination that the degree of certainty is above the threshold value. ### Claim 2 (depends on 1) The unmanned vehicle of claim 1, wherein selecting the one or more uncertainty propagation models comprises selecting one or more kinematic models, dynamic models, and/or extrinsic models. ### Claim 3 (depends on 1) The unmanned vehicle of claim 1, wherein the processor is further configured to determine that the enumerated unmanned vehicle capabilities support a performance level threshold, and subsequently enable the autonomous calibration mode based on the determination that the one or more enumerated unmanned vehicle capabilities satisfies the performance level threshold. ### Claim 4 (depends on 1) The unmanned vehicle of claim 1, wherein the processor is further configured to process the sensor data using one or more uncertainty propagation models to determine the degree of certainty of one or more of: a respective calibration of a relationship between uncertainty on sensor measurements with respect to the position of the chassis; a respective location of each of the one or more sensors with respect to the chassis; a respective orientation of each of the one or more sensors with respect to the chassis; and, one or more of respective shapes and respective location of sensed features. ### Claim 5 (depends on 1) The unmanned vehicle of claim 1, wherein the one or more sensors comprise one or more of: cameras, LIDAR (Light Detection and Ranging) devices, laser sensing devices, radar devices, accelerometers, and magnetometers. ### Claim 6 (depends on 1) The unmanned vehicle of claim 1, wherein the threshold value comprises a respective constraint on one or more of: a control algorithm, a mapping algorithm, a localization algorithm, at least one performance capability, and at least one current probability distribution. ### Claim 7 An unmanned vehicle comprising: a chassis; a processor for controlling a propulsion system of the unmanned vehicle and receiving sensor data from one or more sensors of the unmanned vehicle, the processor is configured told: enumerate one or more unmanned vehicle capabilities by querying one or more of the propulsion system and the one or more sensors of the unmanned vehicle; operate the propulsion system in an autonomous calibration mode by: automatically controlling the propulsion system to move the chassis; collecting the sensor data from the one or more sensors; selecting one or more uncertainty propagation models from a plurality of uncertainty propagation models based on at least one of i.) one or more unmanned vehicle capabilities and ii.) the sensor data; and processing the sensor data using the one or more uncertainty propagation models to determine at least one degree of certainty on a calibration of one or more of the sensor data and a position of the chassis; determine that the degree of certainty is above a threshold value; and subsequently switch operation of the propulsion system to an operational mode based on the determination that the degree of certainty is above the threshold value. ### Claim 8 (depends on 7) The unmanned vehicle of claim 7, wherein the enumerating the one or more unmanned vehicle capabilities comprises one or more of: receiving sensor capability data; and autodetecting sensor capability data. ### Claim 9 (depends on 7) The unmanned vehicle of claim 7, wherein the processor is further configured to determine that the enumerated unmanned vehicle capabilities support a performance level threshold, and subsequently enable the autonomous calibration mode based on the determination that the one or more enumerated unmanned vehicle capabilities satisfies the performance level threshold. ### Claim 10 An unmanned vehicle comprising: a chassis; a communication interface; and a processor for controlling a propulsion system of the unmanned vehicle and receiving sensor data from one or more sensors of the unmanned vehicle, the processor is configured to: prior to entering an guided calibration mode, enumerate unmanned vehicle capabilities, by one or more of: receiving a weight of the unmanned vehicle; receiving one or more dimensions of the unmanned vehicle; autodetecting each of the one or more sensors; receiving a list of the one or more sensors; and using a scanner to scan one or more graphical identifiers of the one or more sensors; in the guided calibration mode, while controlling the propulsion system according to commands received via the communications interface from an external guided control system, select one or more uncertainty propagation models from a plurality of uncertainty propagation models based on at least one of i.) one or more unmanned vehicle capabilities and ii.) the sensor data and, process the sensor data using the one or more uncertainty propagation models to determine at least one degree of certainty on a calibration of one or more of the sensor data and a position of the chassis; determine that the degree of certainty is above a threshold value associated with a safe operation of the propulsion system in an autonomous calibration mode; and subsequently switch operation of the propulsion system to the autonomous calibration mode based on the determination that the degree of certainty is above the threshold value. ### Claim 11 (depends on 10) The unmanned vehicle of claim 10, wherein selecting the one or more uncertainty propagation models comprises selecting one or more kinematic models, dynamic models, and/or extrinsic models. ### Claim 12 (depends on 10) The unmanned vehicle of claim 10, wherein the processor is further configured to determine that the enumerated unmanned vehicle capabilities support a performance level threshold, and subsequently enable the guided calibration mode based on the determination that the enumerated unmanned vehicle capabilities satisfies the performance level threshold. ### Claim 13 (depends on 10) The unmanned vehicle of claim 10, wherein the processor is further configured to process the sensor data using one or more uncertainty propagation models to determine the degree of certainty of one or more of: a respective calibration of a relationship between uncertainty on sensor measurements with respect to the position of the chassis; a respective location of each of the one or more sensors with respect to the chassis; a respective orientation of each of the one or more sensors with respect to the chassis; and, one or more of respective shapes and respective location of sensed features. ### Claim 14 (depends on 10) The unmanned vehicle of claim 10, wherein the one or more sensors comprise on or more of: cameras, LIDAR (Light Detection and Ranging) devices, laser sensing devices, radar devices, accelerometers, and magnetometers. ### Claim 15 (depends on 10) The unmanned vehicle of claim 10, wherein the threshold value comprises a respective constraint on one or more of: a control algorithm, a mapping algorithm, a localization algorithm, at least one performance capability, and at least one current probability distribution. ### Claim 16 An unmanned vehicle comprising: a chassis; a communication interface; and a processor for controlling a propulsion system of the unmanned vehicle and receiving sensor data from one or more sensors of the unmanned vehicle, the processor is configured to: enumerate one or more unmanned vehicle capabilities by querying one or more of the propulsion system and the one or more sensors of the unmanned vehicle; in the guided calibration mode, while controlling the propulsion system according to commands received via the communications interface from an external guided control system, select one or more uncertainty propagation models from a plurality of uncertainty propagation models based on at least one of i.) one or more unmanned vehicle capabilities and ii.) the sensor data and, process the sensor data using the one or more uncertainty propagation models to determine at least one degree of certainty on a calibration of one or more of the sensor data and a position of the chassis; determine that the degree of certainty is above a threshold value associated with a safe operation of the propulsion system in an autonomous calibration mode; and subsequently switch operation of the propulsion system to the autonomous calibration mode based on the determination that the degree of certainty is above the threshold value. ### Claim 17 (depends on 16) The unmanned vehicle of claim 16, wherein the enumerating the unmanned vehicle capabilities comprises one or more of: receiving sensor capability data; and autodetecting sensor capability data. ### Claim 18 (depends on 16) The unmanned vehicle of claim 16, wherein the processor is further configured to determine that the enumerated one or more unmanned vehicle capabilities support a performance level threshold, and subsequently enable the guided calibration mode based on the determination that the enumerated one or more unmanned vehicle capabilities satisfies the performance level threshold. ### Claim 19 An unmanned vehicle comprising: a chassis; a communication interface; and a processor for controlling a propulsion system of the unmanned vehicle and receiving sensor data from one or more sensors of the unmanned vehicle, the processor configured to: in a guided calibration mode, while controlling the propulsion system according to commands received via the communications interface from an external guided control system, select one or more uncertainty propagation models from a plurality of uncertainty propagation models based on at least one of i.) one or more unmanned vehicle capabilities and ii.) the sensor data and, process the sensor data using the one or more uncertainty propagation models to determine at least one degree of certainty on a calibration of one or more of the sensor data and a position of the chassis; automatically switch operation of the propulsion system to an autonomous calibration mode when the degree of certainty is above a first threshold value associated with a safe operation of the propulsion system in the autonomous calibration mode; in an autonomous calibration mode, while automatically controlling the propulsion system to move the chassis, collecting the sensor data from the one or more sensors; and further processing the sensor data using the one or more uncertainty propagation models to determine at least one further degree of certainty on the calibration; and automatically switch operation of the propulsion system to an operational mode when the further degree of certainty is above a second threshold value greater than the first threshold value. ### Claim 20 (depends on 19) The unmanned vehicle of claim 19, wherein selecting the one or more uncertainty propagation models comprises selecting one or more kinematic models, dynamic models, and/or extrinsic models.