Patent Description:
Property maintenance tasks are commonly performed using various tools and/or machines that are configured for the performance of corresponding specific tasks. Some of those tools, like chainsaws, are designed to be effective at cutting trees in situations that could be relatively brief, or could take a long time including, in some cases, a full day of work. When operating a chainsaw for a long period of time, fatigue can play a role in safe operation of the device. However, regardless of how long the operator uses the device, it is important that the operator remain vigilant to implementing safe operating procedures in order to avoid injury to himself/herself and to others.

To help improve safety, operators are encouraged to wear protective clothing and other personal protective equipment (PPE). However, some operators may find the PPE to be uncomfortable and, depending on the weather, may work with very thin clothes on their upper bodies. Accordingly, it may be desirable to define additional "intelligent" protection solutions that do not rely on PPE in order to protect users of chainsaws and other outdoor power equipment.

<CIT> discloses a chain saw 3D positional monitoring and anti-kickback actuation system that includes a signal processor receiving, generating and processing signals from multidimensional relative distances measurement modules and adjusts an electromechanical interface with the cutting device drive or power mechanism as well as actuators to counteract dangerous movements of the chainsaw.

Some example embodiments may provide a system for protecting an operator of a power tool. According to the invention, the system includes a first set of wearable sensors worn by the operator, a second set of wearable sensors worn by the operator, a first tool sensor disposed at the power tool where the first tool sensor is configured to communicate with the first set of wearable sensors, a second tool sensor disposed at the power tool where the second tool sensor is configured to communicate with the second set of wearable sensors, and a controller. The controller is configured to determine, based on distances between the first tool sensor and the first set of wearable sensors and between the second tool sensor and the second set of wearable sensors, whether to initiate a protective action with respect to the power tool.

In one example embodiment, another system for protecting an operator of a power tool may be provided. The system may include a plurality of distance sensors worn by the operator, a reader disposed at the power tool, and a controller configured to determine, based on distances between each of the distance sensors and the reader, whether to initiate a protective action with respect to the power tool. The controller may be configured to perform an adaptive power control cycle to determine the distances between each of the distance sensors and the reader.

In another example embodiment, yet another system for protecting an operator of a power tool may be provided. The system may include a plurality of inertial measurement unit (IMU)-based sensors worn by the operator, a tool position sensor disposed at the power tool, and a controller. The controller may be configured to determine, based on measurements between the IMU-based sensors and the tool position sensor, whether to initiate a protective action with respect to the power tool. The IMU-based sensors and the tool position sensor may be periodically calibrated based on predefined poses of the operator and corresponding positions of the power tool.

Some example embodiments may improve the user experience, safety, and/or productivity during use of outdoor powered equipment.

Having thus described some example embodiments in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:.

Some example embodiments now will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all example embodiments are shown. Indeed, the examples described and pictured herein should not be construed as being limiting as to the scope, applicability or configuration of the present disclosure. Rather, these example embodiments are provided so that this disclosure will satisfy applicable legal requirements. Furthermore, as used herein, the term "or" is to be interpreted as a logical operator that results in true whenever one or more of its operands are true. As used herein, operable coupling should be understood to relate to direct or indirect connection that, in either case, enables functional interconnection or interaction of components that are operably coupled to each other.

Some example embodiments may provide for an intelligent protection system that is configured to monitor a position of the guide bar or blade (or other working assembly) of the chainsaw (or other power equipment) relative to body parts of the user. The system is configured to detect when the user's body parts come too close to the guide bar or blade, or otherwise detect when situations arise for which stopping of the chain is desirable. Both the user and the PPE can therefore be protected during operation of various types of cutting equipment.

With respect to the goal discussed above, one solution may be to place inertial measurement unit (IMU) based tracking sensors on the device (e.g., near the guide bar or blade) and on the body parts that are to be protected. IMU based sensors may include three axis accelerometers, gyroscopes and/or magnetometers in order to track movement in three dimensions. This type of tracking is commonly employed in ergonomic and sports research, and is used for special effects in movies and computer games, in order to track body motion. Putting sensors also on or near the guide bar or blade would enable the body motion to be tracked relative to the guide bar or blade, so that protective actions could be prescribed when such tracking indicated a potential intersection between the guide bar or blade and a part of the body. Moreover, volumes could be modeled around each of the body parts and the guide bar or blade in order to define protected volumes (e.g., defined by the body part (or other object) and a predetermined distance around the body part/object) that, when breached, cause protective actions to be implemented.

However, there are known accuracy issues associated with IMU based tracking sensors. In this regard, pure-IMU based displacement calculation solutions (i.e., dead reckoning) introduce calculation errors due to inaccuracy of the sensors, noise, and limitations associated with the calculation platform. Accordingly, some example embodiments may define a system that enables the calibration of IMU-based tracking sensors so that calibrated motion tracking may be enabled. Additionally or alternatively, the IMU-based tracking sensors may be combined with other sensors (e.g., distance measurement sensors) to define a system that employs sensor fusion for improved accuracy with respect to tracking and protective function initiation.

By improving accuracy, and by providing redundancy, a future possibility of defining a system that is both accurate and reliable enough to be operated without PPE can potentially be realized. As such, example embodiments may include the provision of sensor fusion with combinations of different types of sensors and tracking mechanisms. Example embodiments may also include the provision of tracking algorithms and/or methods that employ sensors for measuring distances accurately using adaptive signal strength measurements.

<FIG> illustrates an intelligent protection system of an example embodiment being applied where the outdoor power equipment is a chainsaw <NUM> having an endless chain <NUM> that rotates about a guide bar to perform cutting operations. As shown in <FIG>, an operator <NUM> wears two sets of wearable sensors. In this regard, the operator <NUM> is wearing a helmet <NUM>, gloves <NUM>, and boots <NUM> as examples of PPE. The sensors may be integrated into the PPE, or may be attached thereto. Of course, the sensors could alternatively be integrated into or attached to other clothing or gear, and at other locations as well. Thus, the specific examples shown in <FIG> should be appreciated as being non-limiting in relation to the numbers of sensors, locations of the sensors, and methods of attaching the sensors to the operator <NUM> and/or the gear of the operator <NUM>.

In this example, the two sets of wearable sensors include a first set of wearable sensors that are IMU-based sensors <NUM>. The IMU-based sensors <NUM> of <FIG> are disposed on the helmet <NUM>, gloves <NUM> and boots <NUM> that the operator <NUM> is wearing, but could be at other locations as well, as noted above. Thus, for example, additional IMU-based sensors <NUM> could be provided at the knees, elbows, chest or other desirable locations on the operator <NUM>. The IMU-based sensors <NUM> may operate in cooperation with a tool position sensor <NUM>, which may be disposed at a portion of the tool (e.g., chainsaw <NUM>). Of note, the tool position sensor <NUM> may itself be an IMU-based sensor and/or may include a set of such sensors. The IMU-based sensors <NUM> and the tool position sensor <NUM> may each be configured to perform motion tracking in three dimensions in order to enable relative positions between body parts at which the IMU-based sensors <NUM> are located and the tool to be tracked. The motion tracking may be performed in connection with the application of motion tracking algorithms on linear acceleration and angular velocity data in three dimensions.

The two sets of wearable sensors also include a second set of wearable sensors that are distance sensors <NUM>. Although the distance sensors <NUM> of this example are shown to be in the same locations on the operator <NUM> that the IMU-based sensors <NUM> have been placed, such correspondence is not necessary. As such, more or fewer distance sensors <NUM> could be provided than IMU-based sensors <NUM>, and the distance sensors <NUM> could be provided at the same or different locations on the operator <NUM>. The distance sensors <NUM> may be configured to operate in cooperation with a tool distance sensor <NUM> that may be disposed at a portion of the tool (e.g., chainsaw <NUM>). In this example, the tool distance sensor <NUM> may be disposed at a guide bar of the chainsaw <NUM> so that distance measurements made between the tool distance sensor <NUM> and one or more of the distance sensors <NUM> are indicative of a distance between the guide bar and the body part on which the corresponding one of the distance sensors <NUM> is being worn. Of note, the tool distance sensor <NUM> may be a single sensor and/or may include a set of such sensors.

As can be appreciated from the descriptions above, the IMU-based sensors <NUM> may be sensors configured to track movement in three dimensions. Meanwhile, the distance sensors <NUM> may be configured to measure or track distances in either two dimensions or simply in one dimension (i.e., straight line distance). In either case, distances or proximity measurements may be performed so that the chainsaw <NUM> (or at least the cutting action thereof) may be disabled based on distance or proximity thresholds that can be defined (e.g., for short distances), or based on combinations of relative motion of body parts and the tool at angular velocities or linear velocities above certain thresholds (e.g., stop delay based distances for larger distances).

In an example embodiment, a controller <NUM> may be disposed at the tool (e.g., chainsaw <NUM>) and, in this case, may be provided within a housing <NUM> of the chainsaw <NUM>. The controller <NUM> may be configured to communicate with the tool position sensor <NUM> and/or the IMU-based sensors <NUM> to perform motion tracking as described herein. In <FIG>, the controller <NUM> and tool position sensor <NUM> are shown to be collocated. However, such collocation is not necessary. Moreover, the tool position sensor <NUM> could be located at any desirable location on the chainsaw <NUM>. Thus, for example, the controller <NUM> may have a wired or wireless connection to the tool position sensor <NUM>. If communications between the IMU-based sensors <NUM> and the controller <NUM> occur, such communication may be accomplished via wireless communication (e.g., short range wireless communication techniques including Bluetooth, WiFi, Zigbee, and/or the like).

The controller <NUM> may also be in communication with the tool distance sensor <NUM>. In this regard, for example, the tool distance sensor <NUM> may be configured to interface with the distance sensors <NUM> to make distance measurements. The tool distance sensor <NUM> may then communicate with the controller <NUM> to provide the distance measurements either on a continuous, periodic or event-driven basis. At one end of the spectrum, continuous distance measurements may be provided to and evaluated by the controller <NUM> at routine and frequent intervals. At the other end of the spectrum, the distance measurements may only be provided when the distance measured is below a threshold (e.g., minimum) distance. In any case, the controller <NUM> may be configured to evaluate the distance measurements relative to initiation of warnings or other protective features that the controller <NUM> may be configured to control. As an example, a chain brake <NUM> of the chainsaw <NUM> could be activated if the distance measured for any one of the distance sensors <NUM> relative to the tool distance sensor <NUM> is below the threshold distance. Alternatively or additionally, a warning may be provided (e.g., audibly, visually, or via haptic feedback). If hearing protection <NUM> is worn by the operator <NUM>, an audible warning could be provided via the hearing protection <NUM>. In some cases, the warning may be provided at a first (and larger distance) threshold being met, and the chain brake <NUM> could be activated for a second (and smaller distance) threshold being met.

The same or a different protection paradigm could also be initiated based on tracking done using the IMU-based sensors <NUM> and the tool position sensor <NUM>. Thus, for example, the controller <NUM> may be configured to evaluate inputs received from either (or both) of the IMU-based sensors <NUM> and the tool position sensor <NUM>, and the distance sensors <NUM> and the tool distance sensor <NUM>. The evaluations may be performed simultaneously or in sequence to result in a fusion of the motion tracking and distance measurement sensors (and functions). However, it should also be appreciated that separate controllers (e.g., separate instances of the controller <NUM>) may be employed for each respective one of the sets of wearable sensors in some examples. Moreover, as will be discussed in greater detail below, the controller <NUM> may be configured to prioritize usage of one or the other of motion tracking (e.g., via the IMU-based sensors <NUM> and the tool position sensor <NUM>) and distance measurement (e.g., via the distance sensors <NUM> and the tool distance sensor <NUM>) in specific contexts. For example, distance measurement related measures may have preference (or take precedence) within a certain range of distances (e.g., short distances), and motion tracking related measures may have preference (or take precedence) within another range of distances (e.g., at larger distances). The controller <NUM> may also be configured to manage calibration of the motion tracking functions of the IMU-based sensors <NUM> and the tool position sensor <NUM>.

The configuration of the controller <NUM> for performing sensor fusion and/or calibration in accordance with an example embodiment will now be described in reference to <FIG>. In this regard, <FIG> shows a block diagram of the controller <NUM> in accordance with an example embodiment. As shown in <FIG>, the controller <NUM> may include processing circuitry <NUM> of an example embodiment as described herein. The processing circuitry <NUM> may be configured to provide electronic control inputs to one or more functional units of the chainsaw <NUM> (e.g., the chain brake <NUM>) or the system (e.g., issuing a warning to the hearing protection <NUM>) and to process data received at or generated by the one or more of the motion tracking and distance measurement devices regarding various indications of movement or distance between the tool and the operator <NUM>. Thus, the processing circuitry <NUM> may be configured to perform data processing, control function execution and/or other processing and management services according to an example embodiment.

In some embodiments, the processing circuitry <NUM> may be embodied as a chip or chip set. In other words, the processing circuitry <NUM> may comprise one or more physical packages (e.g., chips) including materials, components and/or wires on a structural assembly (e.g., a baseboard). The structural assembly may provide physical strength, conservation of size, and/or limitation of electrical interaction for component circuitry included thereon. The processing circuitry <NUM> may therefore, in some cases, be configured to implement an embodiment of the present invention on a single chip or as a single "system on a chip. " As such, in some cases, a chip or chipset may constitute means for performing one or more operations for providing the functionalities described herein.

In an example embodiment, the processing circuitry <NUM> may include one or more instances of a processor <NUM> and memory <NUM> that may be in communication with or otherwise control other components or modules that interface with the processing circuitry <NUM>. As such, the processing circuitry <NUM> may be embodied as a circuit chip (e.g., an integrated circuit chip) configured (e.g., with hardware, software or a combination of hardware and software) to perform operations described herein. In some embodiments, the processing circuitry <NUM> may be embodied as a portion of an onboard computer housed in the housing <NUM> of the chainsaw <NUM> to control operation of the system relative to interaction with other motion tracking and/or distance measurement devices.

Although not required, some embodiments of the controller <NUM> may employ or be in communication with a user interface <NUM>. The user interface <NUM> may be in communication with the processing circuitry <NUM> to receive an indication of a user input at the user interface <NUM> and/or to provide an audible, visual, tactile or other output to the operator <NUM>. As such, the user interface <NUM> may include, for example, a display, one or more switches, lights, buttons or keys, speaker, and/or other input/output mechanisms. In an example embodiment, the user interface <NUM> may include the hearing protection <NUM> of <FIG>, or one or a plurality of colored lights to indicate status or other relatively basic information. However, more complex interface mechanisms could be provided in some cases.

The controller <NUM> may employ or utilize components or circuitry that acts as a device interface <NUM>. The device interface <NUM> may include one or more interface mechanisms for enabling communication with other devices (e.g., the tool position sensor <NUM>, the tool distance sensor <NUM>, the chain brake <NUM>, the hearing protection <NUM>, the IMU-based sensors <NUM>, and/or the distance sensors <NUM>). In some cases, the device interface <NUM> may be any means such as a device or circuitry embodied in either hardware, or a combination of hardware and software that is configured to receive and/or transmit data from/to components in communication with the processing circuitry <NUM> via internal communication systems of the chainsaw <NUM> and/or via wireless communication equipment (e.g., a one way or two way radio). As such, the device interface <NUM> may include an antenna and radio equipment for conducting Bluetooth, WiFi, or other short range communication, or include wired communication links for employing the communications necessary to support the functions described herein.

In <FIG>, the tool position sensor <NUM> and/or the IMU-based sensors <NUM> may be part of or embodied as a first sensor network <NUM>, and the tool distance sensor <NUM> and/or the distance sensors <NUM> may be part of or embodied as a second sensor network <NUM>. Thus, the first and second sensor networks <NUM> and <NUM> may be in communication with the controller <NUM> via the device interface <NUM>. However, other direct or other indirect connection or communication mechanisms could be provided in some cases.

The processor <NUM> may be embodied in a number of different ways. For example, the processor <NUM> may be embodied as various processing means such as one or more of a microprocessor or other processing element, a coprocessor, a controller or various other computing or processing devices including integrated circuits such as, for example, an ASIC (application specific integrated circuit), an FPGA (field programmable gate array), or the like. In an example embodiment, the processor <NUM> may be configured to execute instructions stored in the memory <NUM> or otherwise accessible to the processor <NUM>. As such, whether configured by hardware or by a combination of hardware and software, the processor <NUM> may represent an entity (e.g., physically embodied in circuitry - in the form of processing circuitry <NUM>) capable of performing operations according to embodiments of the present invention while configured accordingly. Thus, for example, when the processor <NUM> is embodied as an ASIC, FPGA or the like, the processor <NUM> may be specifically configured hardware for conducting the operations described herein. Alternatively, as another example, when the processor <NUM> is embodied as an executor of software instructions, the instructions may specifically configure the processor <NUM> to perform the operations described herein.

In an example embodiment, the processor <NUM> (or the processing circuitry <NUM>) may be embodied as, include or otherwise control the operation of the controller <NUM> based on inputs received by the processing circuitry <NUM>. As such, in some embodiments, the processor <NUM> (or the processing circuitry <NUM>) may be said to cause each of the operations described in connection with a calibration module <NUM> and a sensor fusion module <NUM> relative to undertaking the corresponding functionalities associated therewith responsive to execution of instructions or algorithms configuring the processor <NUM> (or processing circuitry <NUM>) accordingly.

In an exemplary embodiment, the memory <NUM> may include one or more non-transitory memory devices such as, for example, volatile and/or non-volatile memory that may be either fixed or re-movable. The memory <NUM> may be configured to store information, data, applications, instructions or the like for enabling the processing circuitry <NUM> to carry out various functions in accordance with exemplary embodiments of the present invention. For example, the memory <NUM> could be configured to buffer input data for processing by the processor <NUM>. Additionally or alternatively, the memory <NUM> could be configured to store instructions for execution by the processor <NUM>. As yet another alternative or additional capability, the memory <NUM> may include one or more databases that may store a variety of data sets. Among the contents of the memory <NUM>, applications may be stored for execution by the processor <NUM> in order to carry out the functionality associated with each respective application. In some cases, the applications may include instructions for motion tracking and distance measurement as described herein, along with calibration and sensor fusion functions.

Calibration functions may be performed by the calibration module <NUM>. In this example, the calibration may only be applicable to the first sensor network <NUM> (i.e., motion tracking). However, calibration of other functions could also or alternatively or additionally be performed. The calibration module <NUM> may be configured to interface with zero relative velocity detection (ZRVD) sensors <NUM> (either directly or via the device interface <NUM>) disposed on the chainsaw <NUM> to facilitate calibration of the motion tracking devices (i.e., the IMU-based sensors <NUM> and the tool position sensor <NUM>). In this regard, the ZRVD sensors <NUM> may include tactile sensors located in the handles (e.g., front handle and rear handle) of the chainsaw <NUM>, accelerometer and/or magnetometer inputs from the chainsaw <NUM> (e.g., associated with the tool position sensor <NUM>) and a sensor on the trigger of the chainsaw <NUM>. Input from the ZRVD sensors <NUM> may be integrated with input from the IMU-based sensors <NUM>, and used to calibrate a motion tracking algorithm employed by the controller <NUM>. In this regard, for example, the calibration process may include resetting velocity and displacement errors that are introduced, and may build up over time, from the IMU-based sensors <NUM>.

In an example embodiment, the ZRVD sensors <NUM> may be used to define (or learn) one or more specific tool and/or body positions (or combinations thereof) that correlate to calibration positions. In this regard, for example, certain positions may have known sensor data associated therewith. Accordingly, the chainsaw <NUM> may be detected as being held in one or more of such positions during a calibration procedure in order to reset to a known state of parts of the sensor data. Given that there may be multiple positions, various different parts of the sensor data may be reset until a full reset is achieved by going through a full sequence of calibration positions.

Accordingly, the user manual or a maintenance manual for the chainsaw <NUM> may list the calibration positions. A calibration mode may be entered, and the corresponding positions may be sequentially cycled through. The calibrated positions may relate to both the chainsaw <NUM> and the operator <NUM> in some cases. Thus, for example, the operator <NUM> (who may be a maintenance technician, or the owner in various cases) may be guided as to the poses to assume with the chainsaw <NUM> while wearing the IMU-based sensors <NUM>. The positions may also or alternatively be sensed by the tactile sensors that may be part of the ZRVD sensors <NUM>. Thus, for example, the ZRVD sensors <NUM> may detect that the operator <NUM> has maneuvered the chainsaw <NUM> to one of the calibration positions based on how the operator <NUM> is holding the chainsaw <NUM>, and/or based on the pressing of the trigger and correlated accelerometer and/or magnetometer readings in order to determine vertical or horizontal orientation of the chainsaw <NUM>. In some cases, the inclusion of multiple ones of the IMU-based sensors <NUM> and sensors on the chainsaw <NUM> (e.g., the ZRVD sensors <NUM>) may ensure sufficient independence to achieve good results. Thus, given that the chainsaw <NUM> may be detected to be in various positions, the calibration can automatically occur when one of the calibrated positions is detected (i.e., not responsive to a guided pose, but during use and responsive to detecting that a pose has been assumed with the chainsaw <NUM>). Detection of position (and specifically of calibration positions) may occur when the operator <NUM> pulls the trigger (or actuates another button or operative member of the chainsaw <NUM>). In some cases, the tactile pressure sensor in the handles of the chainsaw <NUM> (as determined by ZRVD sensors <NUM>) may be used to determine a position of the hands relative to determining a current pose of the operator <NUM> and/or position of the chainsaw <NUM>.

In some cases, the calibration procedure may be a part of routine maintenance with a prescribed periodicity. However, the calibration procedure can also or alternatively occur automatically when a calibrated position is detected (either every time, or if calibration in the corresponding calibrated position has not been performed within a given threshold period of time). The calibration algorithm may be configured to perform a double integration of acceleration for linear displacement, gyro data for direction, and Kalman filtering for improved prediction of motion tracking by error correction.

<FIG> illustrates a schematic view of a calibration position of an example embodiment. As shown in <FIG>, the chainsaw <NUM> may be detected as being held in a particular pose by an operator with the IMU-based sensors <NUM> at known locations (based on the particular pose). In some cases, the IMU-based sensors <NUM> may be affixed at (e.g., mounted within) fixed or known locations on PPE such as a jacket or legwear. In this example, the IMU-based sensors <NUM> include a left glove sensor <NUM> and a left elbow sensor <NUM>, a right glove sensor <NUM> and a right elbow sensor <NUM>. However, it should be appreciated that other sensors at other locations could also be included. Thus, the locations and specific sensors shown are merely provided to facilitate explanation of an example embodiment, and are not intended to limit example embodiments.

As can be appreciated from <FIG>, a distance <NUM> from the end of the bar of the chainsaw <NUM> to the left glove sensor <NUM>, which would be known to be on the front handle of the chainsaw <NUM> may be known. As mentioned above, one or more tactile sensors <NUM> (e.g., as part of the ZRVD sensors <NUM>) may be disposed on the front handle to confirm the specific location of the left hand of the operator (and/or the left glove sensor <NUM>). The distance <NUM> from the left glove sensor <NUM> to the left elbow sensor <NUM> may also be known, particularly for the designated pose. Similarly, one or more tactile sensors <NUM> (again examples of the ZRVD sensors <NUM>) may be disposed at the rear handle of the chainsaw <NUM>. The tactile sensors <NUM> may confirm the specific location of the right hand of the operator (and/or the right glove sensor <NUM>). Meanwhile, the distance <NUM> from the right glove sensor <NUM> to the right elbow sensor <NUM> may also be known, particularly for the designated pose. A distance <NUM> from the end of the bar of the chainsaw <NUM> to the right glove sensor <NUM>, and a distance <NUM> between the tactile sensors <NUM> and <NUM>, may also be known. Accordingly, with the known distances (<NUM>, <NUM>, <NUM>, <NUM> and <NUM>), and stored baseline data associated with the pose, the IMU-based sensors <NUM> can be calibrated.

<FIG> is a block diagram of a calibration method in accordance with an example embodiment. As shown in <FIG>, baseline data may be gathered for one or more poses at operation <NUM>. The baseline data may include information associated with roll, pitch, yaw, and other variables of interest including acceleration and velocity information for poses that include motion. At operation <NUM>, the operator <NUM> may be guided through each of the one or more poses in order to obtain current data for comparison to the baseline data or the operator <NUM> may be sensed/detected in any of the one or more poses. Thereafter, at operation <NUM>, the controller <NUM> may reset errors associated with the IMU-based sensors <NUM> based on the comparison, for any or all applicable poses.

As noted above, in some cases, the variables defined may vary (e.g., X/Y/Z, roll/pitch/yaw, Euler, Quaternions, etc.) depending on the specific implementation. Other variables may include device state, and/or a global data-structure variable including acceleration, velocity, angular velocity, position, gyro readings, etc., that can be used for sensor fusion (e.g., by the sensor fusion module <NUM>). Based on the distances mentioned above, various local variables such as the calculated displacement (CalcDis), calculated orientation (CalcOri), and calculated velocity (CalcVel) may be measured or determined. For an example calculation for calibrated motion tracking, the following calculations could serve as one example program, which could be employed. State := Init() //Initiation, measured position
matrix based on known hand positions on handles
combined with accelerometer and magnetometer readings for orientation, reinforced with
machine learning (ML)-based training set data, and for init state in adviced position//
Loop While (On)
Calculate()
Function Calculate() (
MeasUpdate(State) //Similar to Init but measurement
that is context adapted, i.e., bias parameters
continuously updated in each step//
//Calculations below use updated parameters from the MeasUpdate step//
CalcVel := ∫(Acceleration) //Calculated Velocity//
CalcDis := Initial displacement + f(CalcVel) //Calculated displacement//
CalcOri := Initial orientation + ∫(Angular velocity) //Calculated orientation//
Est := Update(CalcDis, CalcOri) //Continuously calculated State//
)
Function MeasUpdate () (
Complex function that implements update bias parameters for state, action and observation data
(e.g., Kalman filter theory)
).

The sensor fusion module <NUM> may be configured to fuse data received by the motion tracking devices (e.g., the IMU-based sensors <NUM> and the tool position sensor <NUM>) and by the distance measurement devices (e.g., the distance sensors <NUM> and the tool distance sensor <NUM>). The data received from the motion tracking devices may be received at the controller <NUM> and processed to determine motion tracking information. The motion tracking information may then be provided to the sensor fusion module <NUM>. As such, when calibrated, the motion tracking information from the motion tracking devices may be considered to be ZRVD-calibrated IMU motion tracking information.

The data received from the distance measurement devices may also be received at the controller <NUM> (either the same or a different instance of the controller <NUM>) and processed to determine distance measurement information. As noted below in reference to the descriptions of <FIG> and <FIG>, the processing for determining the distance measurement information could take a number of different forms. Regardless of the form, the distance measurement information may then also be provided to the sensor fusion module <NUM>. The sensor fusion module <NUM> may be configured to process the distance measurement information and the motion tracking information based on a set of fusion rules. The fusion rules may be generated based on an understanding that the distance measurement information may be more accurate for close range distances, and the motion tracking information may be most useful for tracking motion when the chainsaw bar is relatively far from any body parts. Thus, the fusion rules may define a hierarchy of priority for the distance measurement information and motion tracking information based on proximity. For example, when a movement toward a body part is detected, as distance decreases, the distance measurement information will have increased authority, and as distance increases, the motion tracking information will have increased authority in relation to determining protective functions (if any).

<FIG> is a block diagram showing an example of fusion rules that may be applied in accordance with an example embodiment. Within the context of <FIG>, the following term definitions apply:.

Within this context, a first rule <NUM> may be defined for the minimum distance allowed for a stationary bar. According to the first rule <NUM>, if Dist<X1, then StopChain. In other words, if the bar is closer than a minimum distance (X1), then the chain <NUM> should be stopped. A second rule <NUM> may be defined for the minimal distance allowed during high velocity motion. According to the second rule <NUM>, if (Motion>Y1, and Dir=bodypart and dist<X2), then StopChain. In other words, if the bar is in motion above a certain velocity (Y1) and the distance to a body part is less than a minimal distance (X2) when motion toward any sensor is detected, then the chain <NUM> should be stopped. A third rule <NUM> may be defined for the maximum allowed motion velocity regardless of distance. According to the third rule <NUM>, if (Motion>Y2, and Dir=bodypart), then StopChain. In other words, if the bar is in motion above a certain velocity (Y2) when motion toward any body part is detected, then the chain <NUM> should be stopped no matter what the current distance happens to be. A fourth rule <NUM> may be defined for the maximum allowed motion velocity regardless of direction. According to the fourth rule <NUM>, if (Motion>Y3), then StopChain. In other words, if the bar is in motion above a certain velocity (Y3), then the chain <NUM> should be stopped no matter what the current distance happens to be, and no matter what the direction of movement of the bar is. This is just one example of a rule set that can be employed.

As noted above, distance measurement information can take multiple forms based on the specific sensors and technologies used to implement the distance measurement devices. In an example embodiment, reader based measurement may be employed in some cases. For example, the tool distance sensor <NUM> may be embodied as an electromagnetic reader (or transponder) that is mounted on the tool (e.g., proximate to the working assembly, or in this case, the chain <NUM> of the chainsaw <NUM>, such as on the guide bar), and may include a main lobe that covers the entire surroundings of the working assembly of the tool (e.g., guide bar and chain <NUM>). The electromagnetic reader may be configured to sense a device (e.g., an electronic tag) using a back-scattering principle. A radio frequency identification (RFID) tag is an example of such a tag. However, the tag could also be active in some cases. In any case, <FIG> illustrates an example reader <NUM> with an electronic tag <NUM> to facilitate further description of such an example.

Referring to <FIG>, the reader <NUM> may utilize power provided by the chainsaw <NUM> to execute an adaptive transmission power algorithm as part of a range determination process. The adaptive transmission power algorithm may include generating an initial detection signal <NUM> for transmission with a modulated code over a carrier wave by raising transmit power until a detection occurs. When the tag <NUM> is within a prescribed distance from the reader <NUM>, and the power level is sufficient, the tag <NUM> will receive sufficient power from the initial detection signal <NUM> transmitted to generate a response <NUM> that is then detected by the reader <NUM>. The response <NUM> will retransmit a code used as an identifier for the tag <NUM> back to the transponder <NUM> to identify the tag <NUM>. Having detected the tag <NUM>, the transponder <NUM> may then reduce the transmit power from the transponder <NUM> to transmit a power reduced signal <NUM> having an incrementally lower value than the initial detection signal <NUM>. If received with sufficient power, the tag <NUM> will send a power reduced response <NUM>. The reader <NUM> will then reduce power again (e.g., incrementally) and repeat the incremental power reductions until no response is received from the tag <NUM>. The signal associated with the last (i.e., lowest) power transmitted, when the tag <NUM> is no longer detected, may be referred to as a distance marker signal <NUM>. When the power of the distance marker signal <NUM> is determined, it can be seen that this power is proportional to distance in a fairly consistent and accurate way.

In this regard, detection range is generally exponentially proportional to the output power or transmit power of the reader <NUM>. Although the specific values may change from antenna to antenna (e.g., reader to reader), the proportionality is fairly consistent. Thus, an accurate mapping of power to detection range may be achieved, and small calibration adjustments may be made for individual antennas. Other correction factors (e.g., for temperature) may also be applicable in some cases. The mappings may be stored in the memory <NUM>, and accessible to the controller <NUM> for determining the distance measurement information. Accordingly, when the distance marker signal <NUM> is determined, the process above can be repeated (as shown by operation <NUM>) to determine additional instances of the distance marker signal <NUM>. Any desirable number of repeated iterations can be completed, and a convergence around a range of powers at which the tag <NUM> is lost may be determined. For example, an average or mean power for distance marker signals may be computed with each, or with a predetermined number of iterations of operation <NUM>. The average or mean power for the distance marker signals may then be correlated to the mapping stored in the memory to determine a range or distance between the corresponding sensor (i.e., the tag <NUM>) and the reader <NUM>. This process can be repeated and cycled through rapidly for each one of the distance sensors <NUM> using a time division scheme.

An example of pseudocode that may be used for simplified range detection is shown below in which context the following term definitions apply:
<IMG>.

As an alternative to using the reader <NUM> and tag <NUM> paradigm described above, time of flight-based measurements may be used in some cases. In this regard, the distance measurement information may be calculated from the time of flight of a transmitted signal if the velocity of the signal is known. For electromagnetic signals (e.g., laser, infrared, radiofrequency), the velocity is known to be the speed of light. In an example in which the tool distance sensor <NUM> is embodied as a laser or infrared light source, the tool distance sensor <NUM> generally transmits the laser or infrared light and then measures the time it takes to receive a reflection from one (or multiples ones) of the distance sensors <NUM>. For sound or audible signals, the velocity is known to be the speed of sound, and the distance sensors <NUM> may be transmitters so that the tool distance sensor <NUM> only measures a one way time of flight. In some cases, to avoid complications associated with the potential for dirt or other objects to block or foul sensors, radio transceivers may be preferred. In such examples, turnaround time (i.e., a two-way time of flight) can be measured by the tool distance sensor <NUM> (acting as a master transceiver).

In any case, when applied over short distances, which is generally the case for the context in which example embodiments operate, time of flight will be in the range of a few nanoseconds for light and radio waves, and therefore requires a relatively high sampling rate in order to achieve good accuracy. As such, some embodiments may employ ultrasound transmitters and receivers (i.e., active, and not passive, ultrasound) since sound travels much slower. The slower wave travel may allow lower sampling frequencies to be employed while still achieving good accuracy.

As yet another alternative for obtaining the distance measurement information, radar based measurements may be employed. In this regard, for example, millimeter wave radar may be employed to provide resistance to both dirt and moisture, along with good accuracy within ranges of <NUM> to <NUM> (which are common in this context). Millimeter wave radar is also relatively fast, and lenses can be added to control radar beams. Advanced signal processing techniques can also be employed to distinguish different objects from each other. In such an example, the tool distance sensor <NUM> may be embodied as a millimeter wave radar sensor configured to detect the distance sensors <NUM> based on returns received responsive to each transmission.

Accordingly, in one example embodiment, a system for protecting an operator of a power tool may be provided. The system may include a first set of wearable sensors worn by the operator, a second set of wearable sensors worn by the operator, a first tool sensor disposed at the power tool where the first tool sensor is configured to communicate with the first set of wearable sensors, a second tool sensor disposed at the power tool where the second tool sensor is configured to communicate with the second set of wearable sensors, and a controller. The controller may be configured to determine, based on distances between the first tool sensor and the first set of wearable sensors and between the second tool sensor and the second set of wearable sensors, whether to initiate a protective action with respect to the power tool.

In some cases, modifications or amplifications may further be employed as optional alterations or augmentations to the description above. These alterations or augmentations may be performed exclusive of one another or in any combination with each other. In some cases, such modifications or amplifications may include (<NUM>), the power tool may be a chainsaw, and the protective action may be activating a chain brake of the chainsaw when one of the first set of wearable sensors or the second set of wearable sensors is within a threshold distance of a respective one of the first tool sensor or the second tool sensor. In an example embodiment (<NUM>), the power tool may be a chainsaw or other power equipment such as power cutters with a blade or chain, and the protective action may be providing an audible or visual warning to the operator when one of the first set of wearable sensors or the second set of wearable sensors is within a threshold distance of a respective one of the first tool sensor of the second tool sensor. In some cases (<NUM>), the first set of wearable sensors may include a plurality of inertial measurement unit (IMU)-based sensors, and the first tool sensor may be a tool position sensor. In such an example, the second set of wearable sensors may include a plurality of distance sensors, and the second tool sensor may be a reader disposed at the power tool. In some embodiments (<NUM>), the IMU-based sensors and the tool position sensor may be periodically calibrated based on predefined poses of the operator and corresponding positions of the power tool. In an example embodiment (<NUM>), the controller may be configured to store baseline data corresponding to known distances from each of the IMU-based sensors to the tool position sensor in each of the predefined poses. In such an example, the controller may be configured to perform a comparison of the baseline data to current data gathered in the predefined poses, and reset errors associated with the IMU-based sensors based on the comparison. In some embodiments (<NUM>), the controller may be configured to obtain distance information from the plurality of distance sensors and the reader, and to obtain motion tracking information from the IMU-based sensors and the tool position sensor. In such an example, the controller may be configured to prioritize the distance information over the motion tracking information within a predefined distance, and prioritize the motion tracking information over the distance information outside the predefined distance. In some cases (<NUM>), the transponder may be a millimeter wave radar sensor with focus lenses for the beam. In an example embodiment (<NUM>), the reader may be a light or ultrasound transmitter, and the controller may be configured to calculate distance information based on time of flight measurements associated with the reader and the plurality of distance sensors. In some cases (<NUM>), the reader may be an electromagnetic reader configured to detect electronic tags, and each of the plurality of distance sensors may be an electronic tag. In some embodiments (<NUM>), the controller may configured to: a) increase transmit power until an instance of the electronic tag is detected, b) reduce power until the instance of the electronic tag is no longer detected, c) repeat steps a) and b) to determine a mean or average power at which the electronic tag is no longer detected, and d) determine a range between the reader and the instance of the electronic tag based on the mean or average power.

In an example embodiment, some, any or all of modifications/amplifications (<NUM>) to (<NUM>) may be employed in any combination with each other. Moreover, in some cases, the system could just include either the first set of wearable sensors, where the sensors are configured to be calibrated (e.g., as in (<NUM>) and (<NUM>) above). In some cases, the system may just include the second set of wearable sensors, where the sensors are configured as in (<NUM>) above.

Claim 1:
A system for protecting an operator (<NUM>) of a power tool, the system comprising:
a first set of wearable sensors (<NUM>) worn by the operator (<NUM>);
a second set of wearable sensors (<NUM>) worn by the operator (<NUM>);
a first tool sensor (<NUM>) disposed at the power tool, the first tool sensor (<NUM>) being configured to communicate with the first set of wearable sensors (<NUM>);
a second tool sensor (<NUM>) disposed at the power tool, the second tool sensor (<NUM>) being configured to communicate with the second set of wearable sensors (<NUM>); and
a controller (<NUM>) configured to determine, based on distances between the first tool sensor (<NUM>) and the first set of wearable sensors (<NUM>) and between the second tool sensor (<NUM>) and the second set of wearable sensors (<NUM>), whether to initiate a protective action with respect to the power tool, characterised in that
the first set of wearable sensors (<NUM>) comprises a plurality of inertial measurement unit (IMU)-based sensors (<NUM>), and the first tool sensor (<NUM>) comprises tool position sensor (<NUM>), and
wherein the second set of wearable sensors (<NUM>) comprises a plurality of distance sensors (<NUM>), and the second tool sensor (<NUM>) comprises a reader (<NUM>) disposed at the power tool, and wherein the
IMU-based sensors (<NUM>) and the tool position sensor (<NUM>) are periodically calibrated based on predefined poses of the operator (<NUM>) and corresponding positions of the power tool.