Systems, apparatuses, and methods to compensate field installation error of TARS device

Abstract

To provide a system, an apparatus, and a method to compensate field installation error of a TARS device.SOLUTION: An exemplary system comprises at least one sensor configured to detect attitude data and one or more processors having a memory, operationally coupled with the at least one sensor. The one or more processors are configured to iteratively adjust an offset error present in attitude data until attitude data is within a linear region. Each iteration receives, from the at least one sensor, the attitude data and determines a plurality of calibration coefficients based at least on the received attitude data using a piecewise linear equation. The plurality of calibration coefficients are applied to the attitude data. Thereafter, an offset error present in the attitude data is adjusted based at least on application of the plurality of calibration coefficients until the attitude data is within the linear region of the piecewise linear equation.SELECTED DRAWING: None

Description

[Technical field]

[0001] FIELD OF THE DISCLOSURE Exemplary embodiments of the present disclosure relate generally to sensors, and more particularly, to systems, apparatus, and methods for compensating for field installation errors in Transportation Attitude Reference System (TARS) devices. [Background technology]

[0002] A Transportation Attitude Reference System (TARS) is a technology used in the field of transportation and vehicle systems to determine and monitor the attitude and / or orientation of a vehicle. For example, a TARS device provides important data regarding the pitch, roll, and yaw angles of a vehicle, which are essential for various applications including navigation, stability control, and safety systems in aircraft, automobiles, ships, and other modes of transportation. Typically, a TARS device includes sensors such as accelerometers and gyroscopes to accurately measure and report the pitch, roll, and yaw angles of a vehicle. In the field of transportation and vehicle technology, integrating a calibrated TARS device into a vehicle is a fundamental step to improve safety and accuracy. The TARS device undergoes calibration during manufacturing. However, when a user mounts the TARS device on a vehicle, offset errors are introduced into the TARS device, which are mounting mounting errors in the X, Y, and Z axis directions. Due to the mounting process, recurring challenges arise, especially offset errors that can cause the TARS device to not deliver accurate data.

[0003] The inventors have identified numerous areas of improvement in existing technologies and processes, which are the subject of the embodiments described herein. Through exerted effort, ingenuity, and innovation, many of these deficiencies, challenges, and problems have been overcome by developing solutions contained in the embodiments of the present disclosure, some examples of which are described in detail herein. Summary of the Invention

[0004] The following presents a summary of some example embodiments to provide a basic understanding of some aspects of the disclosure. This summary is not an extensive overview and is not intended to identify key or critical elements or to delineate the scope of such elements. It will be understood that the scope of the disclosure encompasses many potential embodiments in addition to those summarized herein, some of which are further described below.

[0005] In an exemplary embodiment, a system is disclosed. The system comprises at least one sensor configured to detect attitude data. Further, one or more processors having a memory are operatively coupled to the at least one sensor. The one or more processors are configured to iteratively adjust an offset error present in the attitude data until the attitude data falls within a linear region. In each iteration, the attitude data including the offset error is received via the at least one sensor, and a plurality of calibration coefficients are determined based on at least the received attitude data. The plurality of calibration coefficients are determined using a piecewise linear equation. Further, in each iteration, the determined plurality of calibration coefficients are applied to the received attitude data. Thereafter, in each iteration, the offset error present in the attitude data is adjusted based on at least the application of the plurality of calibration coefficients until the attitude data falls within a linear region.

[0006] In some embodiments, the attitude data includes at least one of angular velocity, acceleration, and inclination of the vehicle. Furthermore, the attitude data is configured to calculate roll / pitch / yaw (RPY) values ​​to adjust for offset errors in the attitude data. In some embodiments, the one or more processors are further configured to perform one or more functions based at least on one or more commands received from a user. Furthermore, the one or more functions include a reset all function, a set function, and an add function. Furthermore, the reset all function corresponds to clearing the determined calibration coefficients to zero. Furthermore, the set function corresponds to replacing the RPY value with the PGN RPY value. Furthermore, the add function corresponds to updating the RPY value with the calibration coefficients determined from the detected attitude data.

[0007] In some embodiments, the one or more processors are configured to receive a command from a user to switch from a normal mode to a compensation mode to adjust for an offset error, further comprising: the normal mode corresponding to detecting attitude data via at least one sensor, and the compensation mode corresponding to adjusting for an offset error present in the attitude data.

[0008] In some embodiments, the at least one sensor comprises a three-axis gyroscope or a three-axis accelerometer. In some embodiments, the plurality of calibration coefficients are based on a piecewise linear equation:

[0009]

number

[0010] In another embodiment, a method is disclosed that iteratively adjusts an offset error present in attitude data until the attitude data falls within a linear region. Each iteration includes receiving attitude data including the offset error via at least one sensor. Further, determining a plurality of calibration coefficients based at least on the received attitude data using a piecewise linear equation. Further, applying the determined plurality of calibration coefficients to the received attitude data. Thereafter, adjusting the offset error present in the attitude data based at least on the application of the plurality of calibration coefficients until the attitude data falls within a linear region.

[0011] The above summary is provided merely for the purpose of summarizing some exemplary embodiments to provide a basic understanding of some aspects of the present disclosure. It should therefore be understood that the above-described embodiments are merely examples and should not be construed in any way to narrow the scope or spirit of the present disclosure. It should be understood that the scope of the present disclosure encompasses many potential embodiments in addition to those summarized herein, some of which are further described below. [Brief description of the drawings]

[0012] Having thus described in general terms certain exemplary embodiments of the present disclosure, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and in which: [Figure 1] 1 illustrates a Transportation Attitude Reference System (TARS) device mounted on a vehicle, according to an exemplary embodiment of the present disclosure. [Diagram 2] 1 illustrates a perspective view of an exemplary TARS device according to various embodiments of the present disclosure. [Diagram 3] 1 illustrates a block diagram of an exemplary TARS device, in accordance with various embodiments of the present disclosure. [Figure 4] 1 illustrates an exemplary table of TARE PGNs, according to an exemplary embodiment of the present disclosure. [Diagram 5]1 illustrates an example table of a TARE command, according to an example embodiment of the present disclosure. [Figure 6] 1 illustrates a flowchart of an exemplary method for compensating for field installation errors in a TARS device, according to an exemplary embodiment of the present disclosure. [Figure 7] 1 illustrates a flowchart of another exemplary method for compensating for field installation errors in a TARS device, according to an exemplary embodiment of the present disclosure. [Figure 8] 1 illustrates an example graph relating to the results of piecewise linear correction of a TARS device, in accordance with an example embodiment of the present disclosure. [Figure 9] 1 illustrates example simulation results of a TARS device, according to an example embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Certain embodiments of the present disclosure will now be described in more detail below with reference to the accompanying drawings, which illustrate some, but not all, embodiments of the present disclosure. Indeed, various embodiments may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements.

[0014] The components illustrated in the figures represent components that may or may not be present in various embodiments of the disclosure described herein, such that an embodiment may include fewer or more components than those shown in the figures without departing from the scope of the disclosure. Some components may be omitted from one or more figures or shown with dashed lines for visibility of the underlying components.

[0015] As used herein, the term "comprising" means including, but not limited to, and should be interpreted in the manner typically used in patent context. The use of broader terms such as "comprises," "includes," and "having" should be understood to provide support for narrower terms such as "consisting of," "consisting essentially of," and "comprised substantially of."

[0016] The phrases "in various embodiments," "in one embodiment," "according to one embodiment," "in some embodiments," and similar phrases generally mean that the particular feature, structure, or characteristic that follows the phrase may be included in at least one embodiment of the present disclosure, and may be included in more than one embodiment of the present disclosure (importantly, such phrases do not necessarily refer to the same embodiment).

[0017] As used herein, the word "example" or "exemplary" means "serving as an example, instance, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

[0018] When the specification states that a component or feature "may include / have," "can include / have," "could include / have," "should include / have," "will include / have," "preferably include / have," "optionally include / have," "typically include / have," "optionally include / have," "for example include / have," "in many cases include / have," or "may include / have" (or other such language), the particular component or feature is not required to be included or have a feature. Such components or features may be optionally included or excluded in some embodiments.

[0019] The present disclosure provides various embodiments of systems, apparatus, and methods for compensating for field installation errors of a Transportation Attitude Reference System (TARS) device. The embodiments can correct for offset errors in the attitude data of a TARS device after the TARS device is mounted on a vehicle. The embodiments can calculate the attitude data and determine a calibration factor using a piecewise linear equation on the attitude data. The embodiments can then apply the correction to the calculated attitude data. The embodiments can iteratively calculate the attitude data and make the determination of the calibration factor until the final output falls within a linear region, which may be one or more thresholds associated with specifications related to the application in which the TARS device 100 is used. Additionally, the embodiments can be integrated into a TARS device mounted on a vehicle to provide a robust and reliable system for improved vehicle stability control.

[0020] FIG 1 illustrates a Transportation Attitude Reference System (TARS) device 100 mounted on a vehicle 102, according to an exemplary embodiment of the present disclosure. FIG 2 illustrates a perspective view of an exemplary TARS device 100, according to an exemplary embodiment of the present disclosure. FIG 1 will be described in conjunction with FIG 2.

[0021] In some embodiments, the TARS device 100 may be a packaged sensor array for reporting attitude data of the vehicle 102. The attitude data may include at least the angular velocity, acceleration, and tilt of the vehicle 102. Additionally, the TARS device 100 may be mounted to, in, or on the vehicle 102. In some embodiments, the vehicle 102 may be, for example, a forestry vehicle, a construction vehicle, a pile driver, a skid steer loader, a mobile crane, a smart leveling hitch, a wheel loader, an excavation vehicle, or any other vehicle known in the art. In one exemplary embodiment, the TARS device 100 may be mounted above the left front tire of a construction vehicle. In another exemplary embodiment, the TARS device 100 may be mounted on the hood of a forestry vehicle. The TARS device 100 may be mounted, for example, on any fixed portion of the vehicle 102 without departing from the scope of the present disclosure.

[0022] Additionally, the TARS device 100 can be configured to determine the pitch, roll, and yaw angles of the vehicle. When a user mounts the TARS device 100 on the vehicle 102, offset errors can be introduced into the TARS device 100. The offset errors can be mounting errors in the X, Y, and Z axes. In some embodiments, the TARS device 100 can be calibrated after mounting on the vehicle 102 to compensate for and / or reduce offset errors in the attitude data of the TARS device 100, as described in more detail herein.

[0023] FIG 3 illustrates a block diagram of an example TARS device 100 according to an example embodiment of the present disclosure. FIG 4 illustrates an example table 400 of TARE PGNs according to an example embodiment of the present disclosure. FIG 5 illustrates an example table of TARE commands according to an example embodiment of the present disclosure. FIG 3 will be described in conjunction with FIG 4-FIG 5.

[0024] TARS device 100 may include at least one sensor 302, one or more processors 304, memory 306, input / output circuitry 308, and / or communication circuitry 310. In an exemplary embodiment, a system or apparatus system may be external to TARS device 100 and communicatively coupled to TARS device 100 to perform one or more of the operations described herein to compensate for field installation errors of TARS device 100.

[0025] The at least one sensor 302 may be configured to detect attitude data of the vehicle 102. For example, in some embodiments, the at least one sensor 302 may be mounted on the vehicle 102. The at least one sensor 302 may include, for example, a three-axis gyroscope and / or a three-axis accelerometer. In some embodiments, the attitude data may include angular velocity, acceleration, and tilt of the vehicle.

[0026] The angular velocity of the vehicle 102 may represent how the angular position or orientation of the vehicle 102 changes over time. The angular position or orientation may include how fast the vehicle 102 rotates around an axis of rotation. The angular position or orientation may also include how fast the axis of rotation itself changes direction. In an exemplary embodiment, a three-axis gyroscope may be used to detect the angular velocity of the vehicle 102.

[0027] In some embodiments, the acceleration of the vehicle 102 may represent the amount of change that the vehicle 102 may increase in speed. In an exemplary embodiment, a three-axis accelerometer may be used to detect the acceleration of the vehicle 102. In some embodiments, the inclination of the vehicle 102 may represent the angle between a horizontal plane and a line connecting the center of gravity of the vehicle and the point where the tires of the vehicle 102 contact the ground. In an exemplary embodiment, a three-axis gyroscope sensor may be used in combination with a three-axis accelerometer to detect the inclination of the vehicle 102.

[0028] Additionally, the detected attitude data may include information on the orientation of the vehicle 102 in three-dimensional space based on the angular velocity, acceleration, and tilt of the vehicle 102. The vehicle orientation may further include measurements related to the roll, pitch, and yaw (RPY) values ​​of the vehicle. Additionally, roll may include the rotation of the vehicle 102 around a longitudinal axis of the vehicle 102. The longitudinal axis may include an imaginary line extending from the front of the vehicle 102 to the rear of the vehicle 102. Additionally, roll may include the tilt of the vehicle 102 to the left or right. Additionally, pitch may include the rotation of the vehicle 102 around a lateral axis of the vehicle 102 that extends from left to right. Pitch may include the movement of the vehicle 102 to pitch forward or backward. Additionally, yaw may include the rotation of the vehicle 102 around a vertical axis of the vehicle 102, which is often considered the "up" axis. In some embodiments, yaw may include the vehicle 102 turning left or right without tilting.

[0029] In some embodiments, the at least one sensor 302 may detect attitude data of the vehicle 102 in real time. In some embodiments, the attitude data may be calculated at a frequency of 100 Hertz (Hz). The attitude data may be detected at periodic intervals. For example, the periodic interval may be one minute. In some embodiments, a low pass filter may be used to remove noise from the detected attitude data. For example, a low pass filter with a 10 Hz and 3 dB cutoff frequency may be used.

[0030] In some embodiments, the TARS device 100 may include one or more processors 304. The one or more processors 304 may be operatively coupled to at least one sensor 302. In various examples, the one or more processors 304 may include suitable logic, circuitry, and / or interfaces operable to execute one or more instructions stored in memory 306 to perform a given operation. In some embodiments, the one or more processors 304 may be configured to decode and execute any instructions received from one or more other electronic devices or servers. The one or more processors 304 may be configured to execute one or more computer-readable program instructions, such as program instructions for performing any of the functions described herein. Additionally, the one or more processors 304 may be implemented using one or more processor technologies known in the art. Examples of processors include, but are not limited to, one or more general purpose processors (e.g., INTEL® or Advanced Micro Devices® (AMD) microprocessors) and / or one or more special purpose processors (e.g., digital signal processors or Xilinx® System On Chip (SOC) Field Programmable Gate Array (FPGA) processors).

[0031] The memory 306 may store a set of instructions and data. In some embodiments, the memory 306 may include one or more instructions executable by one or more processors 304 to perform certain operations. It is clear to one skilled in the art that the one or more instructions stored in the memory 306 enable the hardware of the system 100 to perform certain operations. Some commonly known memory implementations include, but are not limited to, fixed (hard) drives, magnetic tapes, floppy diskettes, optical disks, Compact Disc Read-Only Memories (CD-ROMs), and magneto-optical disks, ROMs, Random Access Memories (RAMs), Programmable Read-Only Memories (PROMs), Erasable PROMs (EPROMs), Electrically Erasable PROMs (EEPROMs), semiconductor memories such as flash memories, magnetic or optical cards, or other types of media / machine-readable media suitable for storing electronic instructions.

[0032] The TARS device 100 may include input / output circuitry 308, which may be in communication with the processor 304 to receive input from a user and / or provide output to a user. In some embodiments, the input / output circuitry 308 may also include a keyboard, a mouse, a joystick, a touch screen, a touch area, soft keys, a microphone, a speaker, or other input / output mechanisms.

[0033] The TARS device 100 may include communications circuitry 310 for communicating with one or more other devices and / or systems. In some embodiments, the communications circuitry 310 may be a device or circuit embodied in either hardware or a combination of hardware and software configured to receive and / or transmit data from and / or to a network and / or any other device, circuit, or module in communication with the TARS device 100. In some embodiments, the communications circuitry 310 may include a plug having multiple terminals that may be connected to another device, apparatus, and / or system. In some embodiments, the communications circuitry 310 may include a network interface to enable communication with, for example, a wired or wireless communication network. For example, the communications circuitry 310 may include one or more network interface cards, antennas, buses, switches, routers, modems, and supporting hardware and / or software, or any other devices suitable for enabling communication over a network. For example, the one or more processors 304 may communicate with a remote device (not shown) via a network interface (not shown) of the communications circuitry 310. The network interface may facilitate a communications link between the one or more processors 304 and the remote device. It should be noted that the network interface may also facilitate communication links between other components of the TARS device 100. Furthermore, the network interface may be a wireless network and / or a wired network. The network interface may be implemented using one or more communication techniques.The one or more communication techniques may include radio waves, Wi-Fi, Bluetooth, ZigBee, Z-wave, Visible Light Communication (VLC), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE), Wireless Local Area Network (WLAN), Infrared (IR) communication, Public Switched Telephone Network (PSTN), radio waves, and other communication techniques known in the art.

[0034] In some embodiments, the remote device may enable a user to send one or more input commands to the one or more processors 304 that are used to adjust offset errors present in the detected attitude data. The one or more input commands may include or be related to, but are not limited to, performing one or more functions, calculating attitude data, determining calibration coefficients, providing one or more values ​​for desired attitude data, resetting calibration coefficients, or executing a "script" of commands at varying time intervals between detection of attitude data or application of calibration coefficients.

[0035] In some embodiments, the remote device may include a smartphone, tablet, laptop, personal computer (PC), smartwatch, or any other computing device known in the art. In one embodiment, a user may use a smartphone or tablet as the remote device. In another embodiment, a dedicated Android or IOS application may be developed to interact with one or more processors 304. Furthermore, the dedicated application may be used to discover, configure, and / or command one or more processors 304.

[0036] As described herein, the one or more processors 304 may be operatively coupled to the at least one sensor 302. Furthermore, the one or more processors 304 may be configured to receive attitude data via the at least one sensor. As described above, the detected attitude data may include information regarding the orientation of the vehicle in three-dimensional space. The orientation of the vehicle may further include measurements related to the roll, pitch, and yaw (RPY) values ​​of the vehicle. The one or more processors 304 may be configured to average the received attitude data. Furthermore, the one or more processors 304 may average the received attitude data at periodic intervals. The one or more processors 304 may average another received attitude data after the periodic interval. For example, the one or more processors 304 may average another received attitude data after one minute.

[0037] In some embodiments, the one or more processors 304 may be configured to determine the plurality of calibration coefficients based at least on the received attitude data. The plurality of calibration coefficients may be determined based at least on an average value of the received attitude data. Furthermore, the plurality of calibration coefficients may be determined using a piecewise linear equation. A piecewise linear equation may be a type of mathematical function consisting of multiple linear segments, where each linear segment is defined over a particular interval. In an exemplary embodiment, the piecewise linear equation is:

[0038]

number

[0039] In some embodiments, in a piecewise linear equation, the piecewise function may represent a series of linear segments. Further, each linear segment may be defined over a particular data set. To estimate values ​​within a particular data set, linear interpolation may be applied to the data set. A linear interpolation for a data set may be composed of pieces of linear interpolation. Further, a linear interpolation for a data set may include a concatenation of linear interpolations between each pair of data sets. As a result, a continuous curve may be obtained. Thus, the linear interpolation may estimate values ​​within each linear interpolation to represent complex relationships. Further, the one or more processors 304 may be configured to apply the determined calibration coefficients to an average value of the received attitude data. In some embodiments, the one or more processors 304 may apply the determined calibration coefficients to roll, pitch, and yaw (RPY) values ​​of the vehicle.

[0040] In some embodiments, the one or more processors 304 may be configured to adjust an offset error present in the detected attitude data based on at least application of the multiple calibration coefficients. The one or more processors 304 may adjust the offset error until the attitude data falls within a linear region of the piecewise linear equation. In some embodiments, the at least one sensor 302 may detect attitude data and the one or more processors 304 may iteratively determine the multiple calibration coefficients until the attitude data falls within a linear region of the piecewise linear equation.

[0041] In some embodiments, the offset error may include a constant error present across all measurements of the at least one sensor 302. The offset error may be a "drift" in the output of the at least one sensor 302. In one example, if the at least one sensor 302 should actually output 24° but instead outputs 26°, the at least one sensor 302 may have an offset error of 2°. Furthermore, the at least one sensor 302 may detect the attitude data and the one or more processors 304 may iteratively determine the calibration coefficients until the attitude data falls within the linear region of the piecewise linear equation. As a result, the attitude data may approach the linear region of the piecewise linear equation and the offset error may decrease with each iteration. Furthermore, the final calibration coefficients may be stored in the memory 306.

[0042] As mentioned above, the remote device may enable a user to send one or more input commands to the one or more processors 304 to adjust for offset errors present in the detected attitude data. Additionally, the one or more processors 304 may receive input commands to perform one or more functions described in conjunction with FIGS.

[0043] Referring to FIG. 4, an exemplary table 400 for TARE PGN is illustrated in accordance with an exemplary embodiment or the present disclosure. TARE may be an offset error. It will be apparent to one skilled in the art that the TARE PGN is a peer-to-peer controller area network (CAN) message according to the SAEJ1939 standard. The TARE PGN may receive TARE commands and detected attitude data information as illustrated in FIG. 5. The TARE PGN may include roll / pitch / yaw (RPY) values. The table 400 may include TARE PGN values ​​used by the TARS device 100. The table 400 may include a destination address (PS). The PS may indicate the address of the system. Additionally, the table 400 may include a requestor address (SA). The SA may indicate the address of the user / remote device. Additionally, the CAN message for each PS and SA may be provided along with the number of bits used in each PS and SA.

[0044] Additionally, a CAN message for roll, pitch, yaw (RPY) may be provided to calculate the RPY value. In some embodiments, the RPY value is expressed as uint16=B H ×2 8 +B L The angle can then be calculated in degrees using the calculated uint16. The angle can then be calculated using the angle(deg) = (uint16-2 15 ) / 100. The angle may indicate the actual output obtained after applying multiple calibration coefficients to the detected attitude data.

[0045] 5, an example table 500 of TARE commands is illustrated in accordance with an example embodiment or the present disclosure. Table 500 may include a TARE command for each roll, pitch, yaw, and all of roll, pitch, and yaw. Each type of TARE command may include two bits. Further, the two bits for "all" may include bit ID positions 7 and 6. Further, the two bits for "roll" may include bit ID positions 5 and 6. The two bits for "pitch" may include bit ID positions 3 and 2. Further, the two bits for "yaw" may include bit ID positions 1 and 0.

[0046] Further, in table 500, the CAN message may include one or more functions. Further, the one or more processors 304 may receive the TARE command to execute one or more functions. The one or more functions may further include 00B, 01B, 10B, and 11B. The 00B CAN message may include a function of "do not operate". The 01B CAN message may include a function of "reset all" or "set all". The 10B CAN message may include a function of "add". The 11B CAN message may include a function of "reserve". The reset all function may correspond to clearing the determined calibration coefficients to 0. The set function may correspond to replacing the RPY value with the PGN RPY value as described herein. The add function may correspond to updating the RPY value with the calibration coefficients determined from the sensed attitude data.

[0047] In various embodiments, the one or more processors are configured to receive a command from a user to switch from a normal mode to a compensation mode to adjust the offset error. The normal mode may correspond to detecting attitude data via at least one sensor. The compensation mode may correspond to adjusting the offset error present in the attitude data. The remote device may include a display to indicate whether the TARS device 100 is in the normal mode or the compensation mode. Additionally, the TARS device 100 may correspond to at least one of the Transportation Attitude Reference System (TARS) devices 100 mounted on the vehicle 102. Thus, the offset error may be adjusted to properly mount the TARS device 100 on the vehicle 102.

[0048] Detection of attitude data and performance of further processing steps may be performed by one or more processors of TARS device 100 using at least one sensor 302 without departing from the scope of this disclosure.

[0049] The above-described components of the TARS device 100 are provided for illustrative purposes only.

[0050] 6 illustrates a flowchart of an example method 600 for compensating for field installation errors of the TARS device 100, according to an example embodiment of the present disclosure. The method 600 iteratively adjusts offset errors present in the attitude data until the attitude data falls within a linear region, where each iteration includes:

[0051] First, in step 602, attitude data is received via at least one sensor 302. The attitude data includes an offset error. In some embodiments, the at least one sensor 302 may be mounted on the vehicle to detect the attitude data. Furthermore, the at least one sensor 302 may detect the attitude data in real time. In some embodiments, the attitude data may include angular velocity, acceleration, and tilt of the vehicle. Furthermore, roll / pitch / yaw (RPY) values ​​are detected from the attitude data. Furthermore, the at least one sensor 302 may include at least a three-axis gyroscope, a three-axis accelerometer. Furthermore, the detected attitude data may be averaged.

[0052] For example, the vehicle 102 is equipped with at least one sensor 302, namely a three-axis gyroscope and a three-axis accelerometer, working in concert. The three-axis gyroscope reports angular velocity of 30 degrees per second, and the three-axis accelerometer reports angular velocity of 2 meters per second. 2 Report the acceleration and the 5 degree inclination.

[0053] Subsequently, in step 604, a plurality of calibration coefficients are determined based on at least the received attitude data using a piecewise linear equation. In some embodiments, the plurality of calibration coefficients are determined based on the piecewise linear equation

[0054]

number

[0055] For example, using one or more processors 104, the system 100 may detect an angular velocity of 30 degrees / second, a velocity of 2 meters / second, 2 Based on an acceleration of 100 rpm and a tilt of 5 degrees, the calibration factors are determined as 3, 2, and 2.

[0056] Subsequently, in step 606, the determined calibration factors are applied to the received attitude data. Additionally, the calibration factors may be applied to an average of the detected attitude data. For example, the one or more processors 104 may apply the determined calibration factors of 3, 2, and 2 to the received attitude data. Additionally, the one or more processors 104 may apply the determined calibration factors of 3, 2, and 2 to the received attitude data. Additionally, the one or more processors 104 may apply the determined calibration factors of 3, 2, and 2 to the received attitude data. 2 to 1.5 meters per second 2 , adjust the inclination from 5.0 degrees to 4.3 degrees.

[0057] Subsequently, in step 608, an offset error present in the attitude data is adjusted based on at least the application of the calibration coefficients until the attitude data falls within the linear region. In some embodiments, the attitude data may be detected and the calibration points may be iteratively determined until the attitude data falls within the linear region. For example, the one or more processors 100 adjust the angular rate offset error from 2 degrees / second to 0.3 degrees / second, resulting in highly accurate attitude data.

[0058] In some embodiments, the method 600 may further include performing, by the one or more processors, one or more functions based at least on one or more commands received from a user, the one or more functions including a reset all function, a set function, and an add function. Further, the reset all function may correspond to clearing the determined calibration coefficients to zero. Further, the set function may correspond to replacing the detected attitude data with an average value of the attitude data detected at periodic intervals. Further, the add function may correspond to updating the detected attitude data with a difference between the average attitude data and the attitude data detected after the periodic interval.

[0059] In some embodiments, the method 600 may further include receiving, by the one or more processors, a command from a user to switch from a normal mode to a compensation mode to adjust for the offset error. Further, the normal mode may correspond to detecting attitude data via at least one sensor, and the compensation mode may correspond to adjusting for an offset error present in the attitude data.

[0060] 7 illustrates a flowchart of an example method 700 for compensating for field installation errors of a TARS device 100, according to an example embodiment of the present disclosure. FIG. 7 will be described in conjunction with FIG.

[0061] First, in step 702, the TARS device 100 is mounted at the required location on the vehicle 102. In some embodiments, the vehicle 102 may be, for example, a forestry vehicle, a construction vehicle, a pile driver, a skid steer loader, a mobile crane, a smart leveling hitch, a wheel loader, an excavation vehicle, or any other vehicle known in the art. In one example, the TARS device 100 may be mounted above the left front tire of the construction vehicle.

[0062] Next, in step 704, the vehicle 102 is moved relative to a flat platform (not shown) as viewed from the TARS device 100. Additionally, the vehicle 102 may be moved relative to the flat platform in order for the TARS device 100 to detect attitude data. The vehicle may be moved in either a forward or reverse direction.

[0063] A compensation command is then triggered in step 706. In some embodiments, a compensation command or a command may be received from a user to switch TARS device 100 from normal mode to compensation mode to adjust for the offset error. A compensation in progress status is then indicated in step 708. When TARS device 100 may be switched to compensation mode, progress including compensation may be visible to the user on the display of the remote device.

[0064] Subsequently, in step 710, attitude data (tilt) at 200 Hz with a 10 Hz low pass filter is detected and an average of the detected attitude data (tilt) data is calculated. Further, the attitude data may be detected by at least one sensor 302 as described in step 602. In some embodiments, the attitude data may include angular velocity, acceleration, and tilt of the vehicle 102. Further, the detected attitude data may be averaged.

[0065] Then, in step 712, a number of calibration coefficients are determined using the piecewise linear equation. Further, the number of calibration coefficients may be determined for the average value of the detected attitude data as described in step 604. Then, in step 714, another attitude data (tilt) at 200 Hz with a 10 Hz low pass filter is detected and the average of the detected attitude data (tilt) data is calculated. Further, more attitude data may be detected and the another detected attitude data may be averaged. Further, the determined number of calibration coefficients may be applied to the detected attitude data as described in step 602.

[0066] Subsequently, it is determined whether the detected pose data is within the linear region of the piecewise linear equation in step 716. In some embodiments, the pose data may be detected and multiple calibration points may be iteratively determined until the pose data falls within the linear region.

[0067] Then, in step 718, the calibration coefficients are discarded. In one case, if the attitude data may not fall within the linear region, the calibration coefficients may be discarded and another calibration coefficient may be determined. Then, in step 720, a compensation completion status is indicated. In another case, if the attitude data falls within the linear region, the compensation mode of the TARS device 100 may be completed. Further, the completion status may be displayed on a display of the remote device. Then, in step 722, the calibration coefficients are stored in memory 302. Further, the final calibration coefficients may be stored in the memory of the TARS device 100.

[0068] It will be understood that methods 600, 700 may be implemented in accordance with one or more embodiments disclosed herein and may be combined or modified as desired or needed. Additionally, steps in methods 600, 700 may be modified, reordered, performed differently, sequentially, in parallel or simultaneously, or otherwise altered as desired or needed.

[0069] The above-described embodiments of the present disclosure may be performed by one or more processors 304 and methods 600, 700 of a TARS device 100 using at least one sensor 302 without departing from the scope of the present disclosure.

[0070] FIG. 8 illustrates an example graph relating to a piecewise linear correction result 800 of the TARS device 100, in accordance with an example embodiment of the present disclosure.

[0071] In some embodiments, attitude data may be detected in one or more regions and multiple calibration coefficients may be iteratively determined. Further, the one or more regions may include 0 to 60 seconds, 60 seconds to 120 seconds, etc. Further, the result 800 may involve finding a region from the one or more regions for which to determine calibration coefficients that bring the detected attitude data within a linear region of the piecewise linear equation.

[0072] As described herein, linear interpolation can be applied to estimate values ​​and obtain a continuous curve. Piecewise linear correction to the sensed attitude data can be applied using linear interpolation. In some embodiments, plot 802 may show the offset error in percentage (%). Additionally, plot 804 may show the output of actual tilt in degrees (°). In some embodiments, the output of actual tilt may be the output obtained after applying multiple calibration factors of the sensed attitude data. Without applying offset correction, the offset error on a TARS device 100 mounted on a vehicle 102 can be as large as 4% which translates to a ±2 degree tilt error in the sensed attitude data.

[0073] Further, the first stage correction 806 from 0 to 60 seconds may result in a 2% offset error resulting in ±0.5 degrees of tilt error. Further, the second stage correction 808 from 60 to 120 seconds may result in a 0.1% offset error resulting in ±0.2 degrees of tilt error. In some embodiments, the tilt offset specification is ±0.2 degrees. In some embodiments, the tilt offset specification may be a specification that allows the detected attitude data to fall within the linear region of the piecewise linear equation. Further, if the second stage correction 808 does not fall within the tilt offset specification, a third stage correction (not shown) may be applied from 120 to 180 seconds, and so on until the offset error is 0%.

[0074] FIG. 9 illustrates example simulation results 900 of a TARS device 100 according to an example embodiment of the present disclosure.

[0075] In some embodiments, a user can send a command via a remote device to switch from normal mode to compensation mode to adjust the offset error. Further, after receiving the command, compensation status 902 can appear as in progress. Further, 0 can indicate normal mode and 3 can indicate compensation mode. As a result, the command can put TARS device 100 into compensation mode to adjust the offset error in the attitude data.

[0076] In some embodiments, the attitude data may be detected repeatedly at a frequency of 200 Hz. The detected attitude data may include roll tilt 904 and pitch tilt 906. Further, roll tilt 904 may be detected in degrees (°). Further, pitch tilt 906 may be detected in degrees. The attitude data may be detected at periodic intervals. For example, the periodic interval may be every minute.

[0077] In some embodiments, the TARS device 100 may average the roll tilt 904 and pitch tilt 906 at periodic intervals. Further, a low pass filter may be used to remove noise from the average value. The average value may be taken as the first average sample at 0 minutes of the compensation status 902. Similarly, another average sample may be obtained. Further, calibration coefficients may be determined for the first average sample and the another average sample using a piecewise linear equation. Further, a correction may be applied to the determined calibration coefficients. The correction may be applied with linear interpolation. In some cases, if the correction does not fall within the linear region, the determined calibration coefficients may be discarded. Also, the average samples of the attitude data may be obtained at periodic intervals. For example, the periodic interval may be every minute.

[0078] The steps described in the above embodiment can be repeated until the correction can fall within the linear region. The correction can then be considered as a final set of calibration coefficients, which can be further stored in memory 306. Furthermore, the remote device can indicate a successful compensation sequence 902. As a result, the TARS device 100 can return from the compensation mode to the normal mode.

[0079] Many variations and other embodiments of the disclosure described herein will be suggested to one skilled in the art to which this disclosure pertains having the benefit of the teachings presented in the foregoing description and the associated drawings. It is therefore to be understood that the disclosure is not limited to the particular embodiments disclosed, and that variations and other embodiments are intended to be included within the scope of the appended claims. Moreover, while the foregoing description and the associated drawings describe example embodiments in the context of certain example combinations of elements and / or features, it is to be understood that different combinations of elements and / or features may be provided by alternative embodiments without departing from the scope of the appended claims. In this regard, for example, combinations of elements and / or features different from those set forth above are also contemplated as may be set forth in the appended claims. Although specific terms have been employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

Claims

1. 1. A system comprising: at least one sensor configured to detect attitude data; and one or more processors having a memory and operably coupled to the at least one sensor, the one or more processors: and configured to iteratively adjust an offset error present in the attitude data until the attitude data is within a linear region, each iteration comprising: receiving the attitude data including the offset error from the at least one sensor; determining a plurality of calibration coefficients based on at least the received attitude data using a piecewise linear equation; applying the determined calibration coefficients to the received attitude data; and and adjusting the offset error present in the attitude data based at least on the application of the plurality of calibration coefficients until the attitude data is within the linear region.

2. 2. The system of claim 1, wherein the attitude data includes at least one of an angular velocity, an acceleration, and a tilt of a vehicle, and the attitude data is configured to calculate a roll-pitch-yaw (RPY) value to adjust for the offset error in the attitude data.

3. iteratively adjusting an offset error present in the attitude data until the attitude data is within a linear region, each iteration comprising: receiving attitude data including the offset error from at least one sensor; determining a plurality of calibration coefficients based on at least the received attitude data using a piecewise linear equation; applying the determined calibration coefficients to the received attitude data; and and adjusting the offset error present in the attitude data based at least on the application of the plurality of calibration coefficients until the attitude data is within the linear region.

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