Light measurement using an autonomous vehicle

Systems, methods, and software to acquire light measurements in a targeted space using an autonomous vehicle, such as an aerial drone, are provided. Examples of targeted spaces include, but are not limited to, stadiums, arenas, racetracks, fields, parking lots, etc. Uses of such systems, software, and/or methods include, but are not limited to, verifying that required light intensity, distribution, camera image quality, and/or other performance metrics are met when commissioning, changing, checking, and approving lighting systems, among other things.

TECHNICAL FIELD

The present invention relates to lighting, and more specifically, to light measurement using an autonomous vehicle.

BACKGROUND

Measuring light levels in a stadium can be critical for several reasons. In the case of a televised sporting event, the ground needs to be properly lit for player visibility, viewing by the attending audience and television cameras. Light level measurements can indicate whether the playing surface is sufficiently illuminated and the light is distributed as required (that is, for uniform distribution, there are no aberrational bright or dark spots). These measurements can also be used to differentiate between issues with the lighting system and ground. For example, what may visually appear from the grandstand as a bright spot on the ground, may in fact be a patch of dry grass or the result of improper mowing.

The measurement process is especially pertinent during the lighting system setup/commissioning phase to verify lighting design and positioning. It is also applicable when the lighting system is changed/upgraded and for routine servicing, testing and verification. Lighting requirements may also need to be verified before approval for certain events. For example, the National Collegiate Athletic Association (NCAA) in the U.S.A. publishes Best Lighting Practices for different sports that need to be verified and approved for televised events. Additionally, the Federation Internationale de Football Association (FIFA) publishes lighting specifications for both televised and non-televised soccer events.

Light level measurements are typically performed manually. A portable light meter, typically measuring in units of foot-candle or lux, is positioned on, or close to, the ground and pointed up towards the sky, lighting system and/or cameras to measure incident light. Measurements are typically performed at multiple positions to ascertain light distribution in addition to the intensity of illumination at any given point.

SUMMARY

Embodiments are directed to systems, methods, and software for using one or more fully or semi-autonomous vehicles (for simplicity, “autonomous vehicle(s)”) to make measurements of lighting conditions in targeted space, such as a stadium, an arena, a sports field, a parking lot, an amusement park, a swimming pool, and an aquarium tank, among many other types of spaces. Fundamentally, there is no limitation on the nature and character of the targeted space, other than the fact that it can be traversed by one or more autonomous vehicles. Uses of such systems, software, and/or methods include, but are not limited to, verifying that required light intensity, distribution, camera image quality, and/or other performance metric(s) is/are met when commissioning, changing, checking, and approving lighting or other systems, among other things. Examples of autonomous vehicles that can be used in conjunction with light-measurement systems and methods disclosed herein include, but are not limited to, unmanned aerial vehicles (such as drones), terrestrial robots and unmanned terrestrial vehicles, and unmanned underwater vehicles, among others. Benefits of making light measurements may include, but are not limited to, collecting light-measurement data quicker than conventional methods and reducing the number of people needed to execute a light-measurement plan, thereby making the process more efficient.

In an embodiment, there is provided a method of taking light-measurement readings within a targeted space. The method includes: receiving, for deployment of an autonomous vehicle having a light-measuring sensor, a light-measuring plan that includes an identification of a plurality of measurement positions for the autonomous vehicle in the targeted space; causing the autonomous vehicle to automatically move to each of the measurement positions based on the light-measuring plan; causing the light-measuring sensor to capture the light measurement at each of the measurement positions while the autonomous vehicle is at the corresponding one of the measurement positions based on the light-measuring plan; and storing, for each measurement position, the light measurement taken at that position and information identifying that position.

In a related embodiment, the targeted space may have a lighting specification that includes the plurality of measurement locations and a corresponding target light-measurement value at each of the measurement locations. In a further related embodiment, the method may further include automatically comparing each light measurement taken to the corresponding target light-measurement value. In another further related embodiment, the targeted space may be a playing field, and the lighting specification may be a FIFA lighting specification.

In another related embodiment, the autonomous vehicle may include an aerial vehicle and the light-measuring plan may include a flight path for the aerial vehicle that traverses a path that includes the plurality of measurement positions. In yet another related embodiment, the autonomous vehicle may include a terrestrial vehicle and the light-measuring plan may include a terrestrial route that traverses a path that includes the plurality of measurement positions. In still another related embodiment, the autonomous vehicle may include a watercraft and the light-measuring plan may include a water-based route that traverses a path that includes the plurality of measurement positions.

In yet still another related embodiment, the method may further include moving the autonomous vehicle to each of the measurement positions using realtime positioning information. In still yet another related embodiment, the method may further include moving the autonomous vehicle to each of the measurement positions based on a local positioning reference.

In still another related embodiment, the method may further include controlling at least one of the autonomous vehicle and a movable mount to achieve an aim for light-measuring sensor. In yet another related embodiment, the light-measuring plan may include a path traversing the measurement positions, and the method may further include determining the path based on a deployment of the autonomous vehicle prior to executing the light-measuring plan.

In another embodiment, there is a non-transitory machine-readable storage medium containing machine-executable instructions configured to cause a processor of a light-measurement system to perform operations including: receiving, for deployment of an autonomous vehicle having a light-measuring sensor, a light-measuring plan that includes an identification of a plurality of measurement positions for the autonomous vehicle; causing the autonomous vehicle to automatically move to each of the measurement positions; causing the light-measuring sensor to automatically capture the light measurement at each of the measurement positions while the autonomous vehicle is the corresponding one of the measurement positions; and storing, for each measurement location, the light measurement taken at that position and information identifying that position.

In a related embodiment, the targeted space may have a lighting specification that includes the plurality of measurement locations and a corresponding target light-measurement value at each of the measurement locations. In a further related embodiment, the operations may further include automatically comparing each light measurement taken to the corresponding target light-measurement value. In another further related embodiment, the targeted space may be a playing field, and the lighting specification may be a FIFA lighting specification.

In another related embodiment, the autonomous vehicle may include an aerial vehicle and the light-measuring plan may include a flight path for the aerial vehicle that traverses a path that includes the plurality of measurement positions. In still another related embodiment, the autonomous vehicle may include a terrestrial vehicle and the light-measuring plan may include a terrestrial route that traverses a path that includes the plurality of measurement positions. In yet another related embodiment, the autonomous vehicle may include a watercraft and the light-measuring plan may include a water-based route that traverses a path that includes the plurality of measurement positions.

In still yet another related embodiment, the operations may further include causing the autonomous vehicle to move to each of the measurement positions using realtime positioning information. In yet still another related embodiment, the operations may further include causing the autonomous vehicle to move to each of the measurement positions based on a local positioning reference.

In still another related embodiment, the operations may further include controlling at least one of the autonomous vehicle and a movable mount to achieve an aim for light-measuring sensor. In yet another related embodiment, the light-measuring plan may include a path traversing the measurement positions and the operations may further include determining the path based on a deployment of the autonomous vehicle prior to executing the light-measuring plan.

In another embodiment, there is provided a light-measuring system to take light measurements within a targeted space. The system includes: an autonomous vehicle that includes locomotion system capable of moving the autonomous vehicle so that it traverses a path that includes measurement positions within the targeted space; a light-measuring sensor deployed on the autonomous vehicle to acquire the light measurement at each of the measurement positions; and a measurement-plan system configured to implement a measurement plan for acquiring the light measurements at the measurement positions, the measurement-plan system including: navigation instructions configured to cause the locomotion means to move the autonomous vehicle so that it traverses the path; and sensor instructions configured to cause the light-measuring sensor to capture the light measurement at each of the measurement positions.

In a related embodiment, the autonomous vehicle may include an aerial vehicle, and the locomotion system may include hovering capability. In another related embodiment, the autonomous vehicle may include a terrestrial vehicle. In yet another related embodiment, the autonomous vehicle may include a watercraft.

In still another related embodiment, the autonomous vehicle may further include a global positioning system receiver, and the navigation instructions may cause the locomotion system to move the autonomous vehicle so that it traverses the path based on global positioning system information acquired by the global positioning system receiver. In yet still another related embodiment, the autonomous vehicle may further include a positioning system that permits the autonomous vehicle to identify each measurement position based on a local positioning reference. In still yet another related embodiment, the light-measuring sensor may be movably mounted to the autonomous vehicle, and the sensor instructions may include instructions to move the light-measuring sensor relative to the autonomous vehicle.

DETAILED DESCRIPTION

FIG. 1illustrates an example light-measuring method100in accordance with aspects of the present disclosure. In general, light-measuring method100provides a method of making light measurements at a plurality of locations within a targeted space, which, as noted above, can be any indoor or outdoor space in which it is desired to collect light-measurement data. It is noted that the nature of the light measurements is not limited in any manner and may be any type of light measurement, such as a photometric measurement, a radiometric measurement, or a spectrographic measurement, among others. It is also noted that more than one type of light measurement can be taken at each of the plurality of locations and that the type of reading(s) can vary among the plurality of locations within any given targeted space. Method100may be implemented using any suitable autonomous-vehicle-based light-measurement system, such as autonomous-vehicle-based light-measurement system200ofFIG. 2. For the sake of illustration, method100is described in the context of autonomous-vehicle-based light-measurement system200. Consequently, references will be made toFIG. 2as well asFIG. 1. To assist the reader, all 100-series numerals in the following description refer toFIG. 1, and all 200-series numerals refer toFIG. 2. Those skilled in the art will understand that the references to autonomous-vehicle-based light-measurement system200relative to method100is merely for convenience and is not intended to limit the scope of the method.

At step105, a light-measurement plan204for an autonomous-vehicle-based light-measurement system, here, autonomous-vehicle-based light-measurement system200is received. In this example, autonomous-vehicle-based light-measurement system200includes an autonomous vehicle208, a light-measuring sensor212mounted to the autonomous vehicle, and a measurement-plan system216that is in communication with the autonomous vehicle and, either directly or indirectly, with the light-measuring sensor. As noted above, autonomous vehicle208may be any suitable fully or semi-autonomous vehicle, depending on the targeted space in which the autonomous vehicle will collect light-measurement data220. As also noted above, light-measuring sensor212may be any suitable light-measuring sensor, such as a light sensor suitable for any one or more desired photometric, radiometric and spectrographic measurements, among others. Again, the singular “light-measuring sensor” is intended to encompass a plurality of light-measuring sensors of the same or differing type. Light-measuring sensor212may be fixedly or movably mounted to autonomous vehicle208in any suitable manner. Regarding movable mounts, such mounts may include rotational mounts, gimbaled mounts, and robotic arm mounts, among others.

Measurement-plan system216may include any collection of software and hardware that provides the requisite functionality. As those skilled in the art will readily appreciate, measurement-plan system216may be embodied in any of a wide variety of forms; consequently, the hardware and software required will vary greatly among at least some of these forms. It is noted that whileFIG. 2illustrates measurement-plan system216as being separate and distinct from autonomous vehicle208, this is in terms of functionality and not physical construct. Indeed, and as described below, one or more portions, or even the entirety, of measurement-plan system216may be physically integrated into autonomous vehicle208. Following are some example forms that measurement-plan system216can take. However, these examples are not exhaustive and are not intended to cover every possibility. That said, those skilled in the art will be able to derive other embodiments using these examples and other information contained in this disclosure without undue experimentation.

Generally, the form that measurement-plan system216takes can depend on the on-board computing power of autonomous vehicle208and the robustness of its user interface228. For example, if autonomous vehicle208contains the entirety of software224and has a robust user interface228that allows a user to directly input light-measurement plan204directly into the autonomous vehicle, then the entire light-measurement-plan system216may reside on the autonomous vehicle primarily in the form of one or more computer processors232, the user interface, and the corresponding software. However, if autonomous vehicle208is configured, for example, to only have enough onboard computing power to receive and execute a vehicle-specific instruction set received from an external device, then light-measurement-plan system216will have more of software224and hardware external to the autonomous vehicle. For example, user interface228and portions of software224responsible for receiving light-measurement-plan204, compiling the light-measurement plan into vehicle-specific instructions, and providing the vehicle-specific instructions to autonomous vehicle208, may reside on a suitable external device (not shown), such as a laptop computer, desktop computer, smartphone, and application-specific device, among others.

Light-measurement plan204includes an identification of a plurality of vehicle positions for autonomous vehicle208to traverse so as to allow the autonomous vehicle to take light measurements at a plurality of light-measurement locations. The light-measurement locations may be user-selected locations or locations prescribed by a light-measurement standard, or a combination thereof. The light-measurement locations may have a dimensionality of one (linear), two (planar), or three (volume) dimension(s). For example, for a 3-D dimensionality and using Cartesian space, each light-measurement location will have x, y, and z coordinates. Each light-measurement location may also have one or more light-sensor directionalities associated therewith. For example, if light-measurement sensor212is directional, i.e., must be aimed in a particular direction, the light-measurement plan204will include information for autonomous vehicle208and/or other mechanism to properly aim the light-measurement sensor while at a particular measurement location.

Depending on whether or not autonomous vehicle208can move freely in 3D space, such as with an aerial drone or underwater vehicle, each corresponding light-measurement position of the autonomous vehicle, will have, for example, either x, y, and z coordinates or x and y coordinates (such as on a horizontal grid), with the z-coordinate (vertical) of the light-measurement location being satisfied by a height of the autonomous vehicle and/or height of light-measuring sensor212. Light-measurement plan204may also include other information, such as one or more paths for autonomous vehicle208to traverse to hit all of the light-measurement locations, directionality of light-measuring sensor212for acquiring a light measurement, an offset distance and/or direction of the light-measurement sensor from the origin of the axes assigned to autonomous vehicle208, information for instructing the light-measuring sensor to take light measurements, and, if the light-measuring sensor is movably mounted to autonomous vehicle208, information for controlling motion of the light-measuring sensor relative to the autonomous vehicle.

At step110, autonomous vehicle208is caused to move to each of the light-measurement positions, for example, by traversing one or more planned movement paths for the autonomous vehicle. Such causation may be brought about in any of a variety of ways. For example, a movement path may be programmed directly into autonomous vehicle208as part of the light-measurement plan if the autonomous vehicle is provided with such functionality or it may be downloaded into the autonomous vehicle from an external device as an instruction set, and the autonomous vehicle may then be triggered to execute the instruction set using any suitable input(s), such as global positioning information or local positioning information, among other things. In some embodiments, movement of autonomous vehicle208may be effected by realtime communication between the autonomous vehicle and a remove vehicle controller (not shown, but seeFIG. 5), which may be fully automated or involve user interaction. As an example of the former, an off-board movement controller may use one or more video cameras or other sensors to observe the movement of autonomous vehicle208and control movements of the autonomous vehicle using information from such observations and knowledge of the light-measurement locations. As an example of the latter, a user may operate a controller that displays, in realtime, the location of autonomous vehicle208and the locations of the light-measurement locations to the user and then allows the user to remotely control movements of the autonomous vehicle based on that visual input. Other manners of performing step110are possible.

At step115, light-measurement sensor212is caused to capture the light measurements when autonomous vehicle208is at the measurement positions. As those skilled in the art will readily appreciate, step115can be performed in any suitable manner. For example, step115can be accomplished automatically via a suitable control instruction set that causes autonomous vehicle208to make a measurement each time the autonomous vehicle is located at or proximate to, within a preset tolerance, a corresponding measurement position. As another example, when control is by a user using, for example, a remote controller to operate autonomous vehicle208and/or light-measuring sensor212, step115may be effected by the user actuating a control on the remote controller that causes the light-measuring sensor to take a light measurement. Such a control can be either a soft control presented on a video display or a hard control, such as a physical button or other control. Those skilled in the art will readily appreciate the variety of ways in which step115can be performed depending on the type and nature of the various component of autonomous-vehicle-based light-measurement system200.

At step120, each light-measurement is stored in a memory236associated with autonomous-vehicle-based light-measurement system200. Memory236may be located at any suitable location, such as onboard autonomous vehicle208or offboard the autonomous vehicle, such as at a remote controller or other device (laptop computer, desktop computer, smartphone, etc.) that is a local component of autonomous-vehicle-based light-measurement system200or on a server remote from the local components of the autonomous-vehicle-based light-measurement system200. Fundamentally, there is no constraint on where memory236is located. Typically, information concerning the light-measurement locations will be stored in memory236in association with the light measurements. Such information may include coordinates (e.g., Cartesian coordinates) of each light-measurement location, a location identifier (e.g., a numeral, an alphanumeric code, a name, etc.), or a combination thereof, among others. With the foregoing generalities in mind, following is a detailed example of implementing method100.

Referring toFIG. 3, in this example method100is implemented in the context of a playing surface300A of a soccer stadium300using an aerial drone304that carries a lux meter308. An exemplar of a systematic approach for light measurement of an area is outlined in the FIFA lighting specifications mentioned in the Background section above. In those specifications and as seen inFIG. 4, a grid400having a 10 m×10 m cell resolution across playing surface300A is used as a basis for collecting the light measurements. For a standard version of soccer stadium300, this typically equates to either 77 (7×11) or 88 (8×11) grid vertices or measurement positions404(only a few labeled to avoid clutter). In a conventional light-measuring scheme, a tripod (not shown) is placed at each of these positions with a light sensor mounted (not shown) level to playing surface300A. A series of measurements are then performed, including: a horizontal measurement at 1 meter above the surface with lux sensor308(FIG. 3) pointing upwards perpendicular to playing surface300A and a vertical measurement at 1.5 meters above the playing surface towards each fixed and field camera point (only one fixed camera312shown inFIG. 3). The measured values are then compared to the horizontal and vertical illuminance and uniformity specifications for compliance.

Based on a review of some surveys for several stadiums in Europe, it typically takes fourteen person-hours of manual labor plus two hours of analysis to complete such a survey for the FIFA lighting specifications. Two people are generally required to reduce the time needed for the manual labor component to one working day.

Referring again toFIG. 3, in this example, lux sensor308is mounted to aerial drone304so that the lux sensor is able to be angled in an unobscured manner towards the sky316in a direction perpendicular to playing surface300A and toward fixed and field cameras (only one fixed camera316illustrated around stadium300. By following an autonomous and systematic flight path408(FIG. 4) that traverses measurement positions404illustrated inFIG. 4, aerial drone304(FIG. 3) is able to rapidly perform a light measurement survey without contacting or interfering with playing surface300A. Aerial drone304can thereby reduce the time, cost and human error/inconsistency associated with current manual approaches, especially for large or high-density surveys.

For example, regarding time, an aerial drone, such as aerial drone304, can traverse measurement grid400(FIG. 4) and angle lux sensor308faster than a human. Each measurement can also be performed within a few seconds and automatically recorded with metadata (including localization and tagging information); no manual data recording is required. Height adjustments of lux sensor308above playing surface300A are innately performed by aerial drone304faster than manually adjusting a tripod and verifying height. Regarding reduced costs, aside from initial calibration/flight plan setup for stadium300, aerial drone304replaces human labor and may require pre-flight setup, post-flight shutdown, and general oversight during operation in terms of safety, performance, and maintenance. Reduced measurement time also reduces stadium downtime and associated opportunity cost.

In addition, there is no interference to playing surface300A. Unlike a manual survey, there is no need for physical grid indicators (not shown), and aerial drone304does not contact or interfere with playing surface300A. This is especially relevant when playing surface300A is being treated, watered, mowed, or marked/painted. Using aerial drone304also reduces the risk of human error and can be programmed to repeatedly follow a flight plan and measurement procedure. On the other hand, manual survey results may partly depend on the person (including his/her experience and skill level, procedural preferences, and state of mind) doing the survey.

In some embodiments, aerial drone304is used as a positioning and angle-measuring tool with telemetry and digital flight plan storage. Aerial drone304may include one or more of a variety of onboard sensors (not shown), such as one or more positioning sensors (e.g., a global positioning system (GPS) sensor, a local reference sensor, etc.), a compass, and an inertial-measurement unit (IMU), among others, that can be additionally used to measure grid400(FIG. 4) of measurement positions404and camera angles to create a flight plan for a new stadium. The flight plan can be digitally stored and thereafter remain static until an associated stadium change is made. Therefore, no additional measurement tools are needed. Conversely, the manual approach requires tools to measure the grid and angles every time.

Light measurements with varying height/altitude specifications are innately accomplished by an aerial drone. Flight paths for a rotary-wing drone, such as aerial drone304, are not dependent on turning circle and kinodynamic constraints like a mobile robot's locomotion mechanism. Thus, a flight plan need not be coupled to a particular drone platform, thereby offering hardware flexibility. While a terrestrial mobile robot can alternatively be used in the scenario ofFIG. 3, the mobile robot's physical contact with the ground can have a destructive effect. In addition, an aerial drone, such as aerial drone304, can be more easily transported than a terrestrial robot.

FIG. 5illustrates an example system configuration500for implementing a light-measurement plan using aerial drone304ofFIG. 3. In this example, system configuration500includes three components, aerial drone304, a radio-control (RC) transmitter504, and a ground control station (GCS)508. As mentioned above, aerial drone304has a light sensor, here lux sensor308, which can be stably angled, for example and under appropriate control, directly vertically upward and towards each of the fixed and field cameras (see, e.g., fixed camera312ofFIG. 3) located around stadium300. This can be achieved by attaching lux sensor308to a side-mounted gimbal mount512, versus the common underslung gimbal mount, to ensure that the sensor's field-of-view is unobstructed by the airframe516and other parts (including, for instance, propellers520) of aerial drone304. Other possible options (not shown) include, but are not limited to: using a top- or side-mounted camera, with or without a gimbal, which can be used to quantify illuminance via image processing and using multiple fixed light sensors mounted at the required angles. Drawbacks of the latter option, however, is that while, for example, FIFA recommends a 30° elevation angle above the horizontal plane for measuring to fixed cameras, such as fixed camera312ofFIG. 3, the angle requirements may be different for different sports or other events, geographic regions and authorities, and, secondly, the true elevation angle to a fixed camera changes depending on sensor position. Thus, this option may not be as flexible under certain circumstances.

As noted above, in this example aerial drone304is also fitted with sensors for localization, including, for example, a GPS524, compass (not illustrated) and an inertial-measurement unit (IMU) (not illustrated), comprising a combination of accelerometers and gyroscopes. There may be, in some embodiments, multiple onboard communication transceivers (not shown), such as, but not limited to, two, three, four, or more. A first one of such communication transceivers links, via communication link528, to RC transmitter504to enable manual pilot control, safety override, telemetry view, arm/disarm and other possible mode controls (such as autonomous flight plan engagement/disengagement). A second one of the onboard communication transceivers links, via communication link532, to GCS508, which may run on a personal computer, a tablet computer, a smartphone, or other device having a graphical user interface. In this example, GCS508is used to: configure aerial drone304(setting, for example, autonomous functionality parameters, flying characteristics, geofence, and other fail-safes); create, store and load a flight plan (part of the measurement plan); monitor the drone via telemetry; and store sensor data for analysis.

FIG. 6illustrates a high-level method600for operating aerial drone304(FIGS. 3 and 5). At step605, it is decided whether or not a measurement plan needs to be created for a particular stadium. If a measurement plan creation method, such as the method described below, has not yet been used for the stadium to be surveyed, or if a measurement plan has been created but the relevant configuration parameters, including surface geometry and fixed camera positions, have changed, then a measurement plan needs to be created at step610. Otherwise, the preexisting digital measurement plan is loaded in a pre-flight procedure at step615. Other pre-flight tasks may include: charged battery installation, sensor calibration, safe takeoff positioning, system checks, and safety procedures. Aerial drone304(FIGS. 3 and 5) is then armed, and autonomous flight engaged. Aerial drone304takes off, executes the measurement plan at step620and lands. At step625, a post-flight procedure is performed. The post-flight procedure may include: disarming aerial drone304, performing system checks, and shutting down. At step630, data analysis and reporting of results may be performed.

In one example, the measurement plan can be created by first using aerial drone304(FIGS. 3 and 5) as a positioning and angle measuring tool. Referring toFIG. 7, to systematically align aerial drone304to each fixed and field camera (see, e.g., fixed camera312ofFIG. 3), a scope700or other sighting system can be first mounted to aerial drone304and its mounting position and orientation, relative to the drone's coordinate system (seeFIG. 4), calculated.FIG. 7depicts scope700mounted to the top of aerial drone304, allowing the aerial drone to be held and aimed in a manner similar to holding a rifle. A user can then look through scope700and orient aerial drone304to bring a targeted camera (such as fixed camera312) into view/coaxial alignment. The resulting telemetry data provides the absolute yaw and pitch angle to the camera with respect to the absolute position of aerial drone304. A button, switch, or other device (none shown) can also be used to aid in tagging telemetry data when aimed for later identification in the telemetry log. Note that the roll angle of aerial drone304is used to correct the yaw and pitch angle calculations and is not otherwise recorded in the measurement plan, as during flight the aerial drone is held level with the ground while taking light measurements.

In an example, to programmatically calculate a flight path for a rectangular surface, aerial drone304is used to measure the absolute position of at least three corners of playing surface300A (FIG. 3) using a positioning sensor, such as a GPS sensor or local reference sensor, possibly data fused with other localization sensor(s) (for instance, IMU). At each of these corners, the yaw and pitch angles to each fixed and field camera (such as fixed camera316ofFIG. 3) are also measured. GCS508(FIG. 5) may then use the corner positions to calculate the perimeter of playing surface300A and grid400(FIG. 4) of measurement positions404(e.g., in terms of GPS waypoints), and the GCS may use the associated sets of angle measurements to calculate the drone yaw/rudder angle and gimbal angle at each measurement position for each measurement. The altitude of aerial drone304(FIGS. 3, 5, and 7) at each measurement position404, similar to the case with the manual approach, can typically be obtained by way of best practices. As noted above,FIG. 4illustrates example flight path408. In the present example, aerial drone304stops at each measurement position404, adjusts its yaw and/or gimbal angle to take each measurement, records the measurements, and then moves to the next measurement position. Note that if measurements are required at different altitudes (i.e., heights above playing surface300A (FIG. 3), it may be advantageous in terms of power consumption for aerial drone304to fly the entirety of flight path408(FIG. 4) for each altitude rather than making altitude shifts at every measurement position.

Upon executing a measurement plan or thereafter, software, in this example aboard GCS508(FIG. 5), can be used to analyze the stored light measurements and telemetry data. Forms of analysis and reporting may include any one or more of the following, among others: tabulated illumination readings, possibly divided according to some dimension (for instance, a fixed or field camera); statistical analysis; problem/anomaly detection; and graphical charts.

Although many shapes are possible, aerial drone304(FIGS. 3, 5, and 7) shown in the drawings has an uncommon “Y6” airframe configuration with a side-mounted gimbal mount512, which provides an unobstructed 180° vertical field-of-view and, thus, the flexibility to measure at any angle. As noted above, scope700(FIG. 7), for use in the flight path setup procedure, is mounted to the top of aerial drone304and functions similar to a rifle scope. As seen inFIG. 8, a duel propeller system800per arm804(1) to804(3) is used for redundancy and safety.FIG. 8also illustrates a set of roll, pitch, and yaw axes808R,808P, and808Y, respectively, as well as exemplar local and global reference frames812and816, respectively.

As an alternative to the aerial-drone-based approach of the foregoing example and as mentioned above, a terrestrial mobile robot can be used. A disadvantage of using a terrestrial mobile robot is the physical contact with playing surface300A (FIG. 3) and potential ground damage. The risk of damage depends on the locomotion mechanism and may increase with speed, especially when turning (as is the case, for instance, with skid steering). Another disadvantage is that if the survey requires light measurements at varying heights/altitudes above the ground, a robot may need to employ a motorized mechanism to achieve this capability, in a limited sense. That is, not all heights will be achievable. Also, transportation of a terrestrial mobile robot, which is generally larger and heavier than an aerial drone, to/from a stadium or other targeted space may be more cumbersome.

A typical advantage of a terrestrial mobile robot, on the other hand, is larger payload and operating time. The former means that potentially a more comprehensive light-measuring sensor or set of sensors, for example, a spectrophotometer that measures light intensity as a function of wavelength, can be employed more readily. Also given an aerial drone's spinning propellers and free-falling weight upon failure, a terrestrial mobile robot can be safer.

A method of using a terrestrial mobile robot would be similar to that outlined above but with some distinct differences. For example, instead of a flight path, a ground path would need to be devised that takes into consideration any turning circle and kinodynamic constraints of the particular locomotion mechanism used. Thus, unlike a rotary-wing aerial drone, a ground path would be closely coupled to a particular robot platform resulting in less hardware flexibility, especially when considering a universal approach. Another difference concerns the light-measuring sensor mount and angle and height control. The light-measuring sensor may need to be mounted on a turret, gimbal, robot arm, and/or other motorized mechanism to provide the required control. A further difference is in the initial ground path setup. While a person can typically carry an aerial drone easily for use as a position and angle measuring tool, a terrestrial mobile robot may not be as easily or quickly moved manually. However, in both the aerial drone and terrestrial mobile robot cases, using birds-eye imagery, for example, satellite imagery, and on-board sensor(s) that can measure angles to stadium cameras using image processing (passive approach) or beacon detection (requiring infrastructure) can be beneficial in terms of a more automated setup.

FIG. 9shows a diagrammatic representation of one embodiment of a computing device in the example form of a computer system900within which a set of instructions may be executed for causing a system, such as any one or more of systems200,216, and500ofFIGS. 2 and 5, and/or portion(s) and/or combinations thereof, to perform any one or more of the aspects and/or methodologies of the present disclosure, such as method100ofFIG. 1and method600ofFIG. 6. It is also contemplated that multiple computing devices may be utilized to implement a specially configured set of instructions for causing one or more of the devices to perform any one or more of the aspects and/or methodologies of the present disclosure. Computer system900includes a processor904and a memory908that communicate with each other, and with other components, via a bus912. Bus912may include any of several types of bus structures including, but not limited to, a memory bus, a memory controller, a peripheral bus, a local bus, and any combinations thereof, using any of a variety of bus architectures.

Computer system900may also include a storage device924. Examples of a storage device (e.g., storage device924) include, but are not limited to, a hard disk drive, a magnetic disk drive, an optical disc drive in combination with an optical medium, a solid-state memory device, and any combinations thereof. Storage device924may be connected to bus912by an appropriate interface (not shown). Example interfaces include, but are not limited to, SCSI, advanced technology attachment (ATA), serial ATA, universal serial bus (USB), IEEE 1394 (FIREWIRE), and any combinations thereof. In one example, storage device924(or one or more components thereof) may be removably interfaced with computer system900(e.g., via an external port connector (not shown)). Particularly, storage device924and an associated machine-readable medium928may provide nonvolatile and/or volatile storage of machine-readable instructions, data structures, program modules, and/or other data for computer system900. In one example, software920may reside, completely or partially, within machine-readable medium928. In another example, software920may reside, completely or partially, within processor904.

Computer system900may also include an input device932. In one example, a user of computer system900may enter commands and/or other information into computer system900via input device932. Examples of an input device932include, but are not limited to, an alpha-numeric input device (e.g., a keyboard), a pointing device, a joystick, a gamepad, an audio input device (e.g., a microphone, a voice response system, etc.), a cursor control device (e.g., a mouse), a touchpad, an optical scanner, a video capture device (e.g., a still camera, a video camera), a touchscreen, and any combinations thereof. Input device932may be interfaced to bus912via any of a variety of interfaces (not shown) including, but not limited to, a serial interface, a parallel interface, a game port, a USB interface, a FIREWIRE interface, a direct interface to bus912, and any combinations thereof. Input device932may include a touch screen interface that may be a part of or separate from display936, discussed further below. Input device932may be utilized as a user selection device for selecting one or more graphical representations in a graphical interface as described above.

A user may also input commands and/or other information to computer system900via storage device924(e.g., a removable disk drive, a flash drive, etc.) and/or network interface device940. A network interface device, such as network interface device940, may be utilized for connecting computer system900to one or more of a variety of networks, such as network944, and one or more remote devices948connected thereto. Examples of a network interface device include, but are not limited to, a network interface card (e.g., a mobile network interface card, a LAN card), a modem, and any combination thereof. Examples of a network include, but are not limited to, a wide area network (e.g., the Internet, an enterprise network), a local area network (e.g., a network associated with an office, a building, a campus or other relatively small geographic space), a telephone network, a data network associated with a telephone/voice provider (e.g., a mobile communications provider data and/or voice network), a direct connection between two computing devices, and any combinations thereof. A network, such as network944, may employ a wired and/or a wireless mode of communication. In general, any network topology may be used. Information (e.g., data, software920, etc.) may be communicated to and/or from computer system900via network interface device940.

Computer system900may further include a video display adapter952for communicating a displayable image to a display device, such as display device936. Examples of a display device include, but are not limited to, a liquid crystal display (LCD), a cathode ray tube (CRT), a plasma display, a light emitting diode (LED) display, and any combinations thereof. Display adapter952and display device936may be utilized in combination with processor904to provide graphical representations of aspects of the present disclosure. In addition to a display device, computer system900may include one or more other peripheral output devices including, but not limited to, an audio speaker, a printer, and any combinations thereof. Such peripheral output devices may be connected to bus912via a peripheral interface956. Examples of a peripheral interface include, but are not limited to, a serial port, a USB connection, a FIREWIRE connection, a parallel connection, and any combinations thereof.

The methods and systems described herein are not limited to a particular hardware or software configuration, and may find applicability in many computing or processing environments. The methods and systems may be implemented in hardware or software, or a combination of hardware and software. The methods and systems may be implemented in one or more computer programs, where a computer program may be understood to include one or more processor executable instructions. The computer program(s) may execute on one or more programmable processors, and may be stored on one or more storage medium readable by the processor (including volatile and non-volatile memory and/or storage elements), one or more input devices, and/or one or more output devices. The processor thus may access one or more input devices to obtain input data, and may access one or more output devices to communicate output data. The input and/or output devices may include one or more of the following: Random Access Memory (RAM), Redundant Array of Independent Disks (RAID), floppy drive, CD, DVD, magnetic disk, internal hard drive, external hard drive, memory stick, or other storage device capable of being accessed by a processor as provided herein, where such aforementioned examples are not exhaustive, and are for illustration and not limitation.

The computer program(s) may be implemented using one or more high level procedural or object-oriented programming languages to communicate with a computer system; however, the program(s) may be implemented in assembly or machine language, if desired. The language may be compiled or interpreted.

As provided herein, the processor(s) may thus be embedded in one or more devices that may be operated independently or together in a networked environment, where the network may include, for example, a Local Area Network (LAN), wide area network (WAN), and/or may include an intranet and/or the internet and/or another network. The network(s) may be wired or wireless or a combination thereof and may use one or more communications protocols to facilitate communications between the different processors. The processors may be configured for distributed processing and may utilize, in some embodiments, a client-server model as needed. Accordingly, the methods and systems may utilize multiple processors and/or processor devices, and the processor instructions may be divided amongst such single- or multiple-processor/devices.

The device(s) or computer systems that integrate with the processor(s) may include, for example, a personal computer(s), workstation(s) (e.g., Sun, HP), personal digital assistant(s) (PDA(s)), handheld device(s) such as cellular telephone(s) or smart cellphone(s), laptop(s), handheld computer(s), or another device(s) capable of being integrated with a processor(s) that may operate as provided herein. Accordingly, the devices provided herein are not exhaustive and are provided for illustration and not limitation.

References to “a microprocessor” and “a processor”, or “the microprocessor” and “the processor,” may be understood to include one or more microprocessors that may communicate in a stand-alone and/or a distributed environment(s), and may thus be configured to communicate via wired or wireless communications with other processors, where such one or more processor may be configured to operate on one or more processor-controlled devices that may be similar or different devices. Use of such “microprocessor” or “processor” terminology may thus also be understood to include a central processing unit, an arithmetic logic unit, an application-specific integrated circuit (IC), and/or a task engine, with such examples provided for illustration and not limitation.

Furthermore, references to memory, unless otherwise specified, may include one or more processor-readable and accessible memory elements and/or components that may be internal to the processor-controlled device, external to the processor-controlled device, and/or may be accessed via a wired or wireless network using a variety of communications protocols, and unless otherwise specified, may be arranged to include a combination of external and internal memory devices, where such memory may be contiguous and/or partitioned based on the application. Accordingly, references to a database may be understood to include one or more memory associations, where such references may include commercially available database products (e.g., SQL, Informix, Oracle) and also proprietary databases, and may also include other structures for associating memory such as links, queues, graphs, trees, with such structures provided for illustration and not limitation.

References to a network, unless provided otherwise, may include one or more intranets and/or the internet. References herein to microprocessor instructions or microprocessor-executable instructions, in accordance with the above, may be understood to include programmable hardware.

Throughout the entirety of the present disclosure, use of the articles “a” and/or “an” and/or “the” to modify a noun may be understood to be used for convenience and to include one, or more than one, of the modified noun, unless otherwise specifically stated. The terms “comprising”, “including” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements.