Autonomous Dust Mitigation in Mining and Construction Applications

Abstract

The autonomous dust mitigation m mmmg and construction applications system disclosed herein may comprise a system that automatically detects dust at mmmg and construction sites and dispatches dust mitigation equipment in response to such detections. The dust areas detected may be assigned priorities within the system, and may be addressed or ignored based on various parameters dictating the behavior of the system. If, for example, an area of dust is not currently in use by local equipment, the system may not dispatch equipment to address that area. If, on the other hand, an area of dust is affecting a high priority or high risk area of the site, the system may prioritize the dispatching of dust mitigation equipment to that area over other areas. The system described in the present invention comprises an autonomous dust mitigation system used in mining and construction applications that contains a plurality of sensors, a computing device, a dust area mapping system, a dust area prioritizing system, and a plurality of dust mitigation equipment.

Claims

1. An autonomous dust mitigation in mining and construction applications system, comprising: a plurality of sensors; a computing device; a dust area mapping system; a dust area prioritizing system; and a plurality of dust mitigation equipment.

2. The system of claim 1, wherein said plurality of sensors detect a plurality of dust area information; wherein said plurality of dust area information includes size, speed, direction, height, relative height, position, and relative position; wherein said plurality of sensors transmit said detected plurality of dust area information to said computing device; wherein said dust area mapping system is installed on said computing device; wherein said dust area mapping system interprets said detected plurality of dust area information to determine a dust area map; wherein said dust area prioritizing system is installed on said computing device; wherein said dust area prioritizing system determines an appropriate dust area priority based on said plurality of dust area information and said determined dust area map; and wherein said computing device instructs said plurality of dust mitigation equipment to perform a dust mitigation.

3. The system of claim 1, wherein said plurality of sensors comprise a LADAR device.

4. The system of claim 1, wherein said plurality of sensors comprise a stereo camera.

5. The system of claim 1, wherein said plurality of sensors comprise a ranging sensor.

6. The system of claim 1, wherein said plurality of sensors comprise a LADAR device.

7. The system of claim 1, wherein said dust area prioritizing system comprises a plurality of environment data.

8. The system of claim 1, wherein said dust area prioritizing system determines an appropriate dust area priority based on said plurality of dust area information, said determined dust area map, and said plurality of environment data; and wherein said computing device instructs said plurality of dust mitigation equipment to perform a dust mitigation.

9. The system of claim 1, wherein the planner coordinates with the overall site planner to deconflict the dust mitigation equipment and the other equipment such as haul trucks.

Description

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0018] Elements in the figures have not necessarily been drawn to scale in order to enhance their clarity and improve understanding of these various elements and embodiments of the invention. Furthermore, elements that are known to be common and well understood to those in the industry are not depicted in order to provide a clear view of the various embodiments of the invention.

[0019] FIG. 1 schematically illustrates the basic autonomous dust mitigation system.

[0020] FIG. 2 illustrates that the dust detection sensors can be mounted at fixed locations.

DETAILED DESCRIPTION OF THE INVENTION

[0021] The following detailed description is merely exemplary in nature and is not intended to limit the described embodiments or the application and uses of the described embodiments. As used herein, the word “exemplary” or “illustrative” means “serving as an example, instance, or illustration.” Any implementation described herein as “exemplary” or “illustrative” is not necessarily to be construed as preferred or advantageous over other implementations. All of the implementations described below are exemplary implementations provided to enable persons skilled in the art to make or use the embodiments of the disclosure and are not intended to limit the scope of the disclosure, which is defined by the claims. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary, or the following detailed description. It is also to be understood that the specific devices and processes illustrated in the attached drawings, and described in the following specification, are simply exemplary embodiments of the inventive concepts defined in the appended claims. Hence, specific dimensions and other physical characteristics relating to the embodiments disclosed herein are not to be considered as limiting, unless the claims expressly state otherwise.

[0022] The present invention uses sensors installed on manned and unmanned vehicles to qualify how the particular dust cloud is affecting a vehicle, and to determine if such an effect interferes with the operation of the vehicle. For example, heavy dust may be present, but it may not deteriorate the performance of the vehicle. On the other hand, light dust may be present, but this dust may be occurring at frequencies that render the vehicle's autonomous systems blind.

[0023] The invention measures the levels of dust detected by the sensors, computes if the levels of dust can affect the performance of the system, and, in the case where the effect warrants the use of water to mitigate the issue, invokes a water dispensing vehicle or sprinklers in needed areas. Both the sensing vehicle and the water vehicle can be autonomous or manned.

[0024] The illustration of FIG. 1 schematically illustrates an autonomous dust mitigation in mining and construction applications system, as contemplated by the present disclosure.

[0025] One method for detecting dust is the single return laser detection and ranging (LADAR), which can see dust as the first return signal sent back to the system. The LADAR hits the surface or edge of the dust cloud, and the dust cloud can be morphologically classified using size, volume, and various movement parameters.

[0026] Another method for detecting dust is by multi-return LADAR, which can partially penetrate through the dust, and, in some cases, can fully penetrate through the dust. As an example, the multiple returns of a single beam can be classified as dust when they return multiple ranges for the same beam. A solid object, in comparison, provides a single range for each beam.

[0027] Cameras, such as electro-optical sensor or infrared cameras, can also see some dust. There are cloud classification algorithms that can correctly classify the dust using the color, size, and texture of particles detected.

[0028] When dust is dense enough, LADARs tend to bloom. The diffracted energy sent into the dust is reflected back to the sensor, usually within the minimum range of the sensor, and tends to overwhelm, or saturate, the receivers, or cause crosstalk in systems with multiple receiver elements. This blooming can be used as a strong indicator that dust is present.

[0029] As the energy radiated by the LADAR bounces off a dust cloud very close to the receiver, the receivers are triggered at very short distances. These very short distances are usually faster than the internal time counters in the LADAR can measure, therefore triggering a “too close” error on the LADAR for each beam embedded in the cloud.

[0030] Redundancy of a variety of sensor combinations. Radio detection and ranging (RADAR) can see through most dust clouds, while and LADAR does not. Therefore, if a combination of these sensors covers the area where the dust cloud is located, the RADAR will show it as transparent and the LADAR will provide returns as if it were solid. These discrepancies between redundant sensors can also be used to detect dust. The redundancy is not only between LADAR and RADAR, but it can also be between two LADARs of different frequencies, a camera and RADAR combination, or any other appropriate combination.

[0031] As the dust is detected, the location of the dust can be determined and stored. The volume and other characteristics of the dust can also be stored such as, for example, density, particulate size, size of cloud, distance from the ground, and other relevant parameters. LADAR can also be used to determine the support surface, as well as the inclination of the ground. If the system detecting the dust is also an autonomous system, it can provide measurements that indicate how the dust, at different locations, is affecting the autonomous system, and may store this information.

[0032] A number of key measurements may affect the performance and safety of the system. As the dust gets denser, less energy will be able to penetrate and reflect from the ground and the distance at which the support surface can be determined is affected. Therefore, the area where the vehicles can determine the support surface for their wheels becomes smaller as the vehicle drives along. For example, a truck may be able to determine its support surface using a LADAR 50 meters in front of the driving area. In a dusty environment, the same system may only be allowed to determine the support surface at 20 meters in front of the vehicle. Depending on the application or the specific environment, 20 meters may or may not be enough. If the maximum speed in the area is less than 5 mph, the vehicle without a load may be able to brake in time if a ditch on the road is detected within the 20 meters. However, if the vehicle is fully loaded and driving at 60 mph, 20 meters may not be sufficient to stop, and, therefore, the vehicle will be unsafe to drive in the dust.

[0033] The distance at which dynamic obstacles are detected, classified, and predicted may also be affected by dust. As with the performance of safety systems, this measurement can be used to compare the reduced sensing and prediction characteristics of the vehicle in dust against the rules of the particular application.

[0034] The distance at which static obstacles are detected and classified may also be affected by dust. The distance at which these obstacles are detected and classified is negatively affected by dust. Measuring how much they are affected by the dust and how this affects the performance of the vehicle becomes important to assess safety within the application.

[0035] It is important to note that, to minimize water usage, it becomes important to track the effects of the dust to the parameters of the autonomous system as it relates to the particular application.

[0036] The invention can be decomposed in two parts: data collection and mitigation effects. During the data collection phase, one or more trucks collect information on the location of the dust, the characteristics of the dust, and the safety assessment. The safety assessment presented above can take into consideration many variables of the user and area, however, simple assessments exist where the user or system may decide to water areas that are above a certain threshold of dust in the many of the measurements taken, or even to use time as a factor in the decision to water an area.

[0037] The information collected is stored in a database. The database is then accessed by a dust mitigation planner algorithm. The dust mitigation planner is an optimization algorithm that generates trajectories and water mitigation needs around the area being groomed. The algorithm can take into consideration a variety of inputs, including the status of the water delivery trucks, as well as all the information collected in the database.

[0038] Optimization can be performed a variety of ways, including simple programming, dynamic programming, and genetic algorithms. The space of optimization can include the cost of the water, cost of reduced performance, chances of losing traction, as well as a large number of utility parameters in the optimization area. Once the optimization is performed, the trucks are sent to water the specified areas.

[0039] While the invention has been described m connection with what is presently considered to be the most practical and preferred embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

[0040] FIG. 1 shows a schematic of the autonomous dust mitigation system in which there are sensors (100) which can be mobile or stationary. These sensors (100) are used to detect the location and dust that is present which is then compared to the dust mapping database. This information is passed along to the dust mitigation planner which looks at the area usage and dust priorities and give trajectories and operation parameters to the dust mitigation equipment controller which is then passed onto the dust mitigation equipment (101, 102).

[0041] FIG. 2 shows that the dust detection sensors (200) can be mounted at fixed locations. These sensors (200) can also be mounted to haul trucks, dust mitigation equipment (201, 202), or other vehicles at the site.

[0042] The autonomous dust mitigation system used in mining and construction applications comprises a plurality of sensors, a computing device, a dust area mapping system, a dust area prioritizing system, and a plurality of dust mitigation equipment.

[0043] The system that is described in the present invention has a plurality of sensors that detect a plurality of dusty area information and the plurality of dust area information includes size, speed, direction, height, relative height, position, and relative position. The plurality of sensors transmit the detect plurality of dust area information to said computing device and the dust area mapping system is installed on the computing device. Also, the dust area mapping system interprets the detected plurality of dust area information to determine a dust area map. Also, the dust area prioritizing system is installed on said computing device and determines an appropriate dust area based on plurality of dust area information and determined dust area map. The computing device instructs the plurality of dust mitigation equipment to perform a dust mitigation.

[0044] The system that is disclosed in the present invention has a plurality of sensors that comprise a LADAR device.

[0045] Laser Detection and Ranging (LADAR) refers to a surveying method that measures distance to a target by illuminating the target with laser light and measuring the reflected light with a sensor. Differences in laser return times and wavelengths can then be used to make digital 3-D representations of the target.

[0046] In another embodiment, the system has a plurality of sensors that comprise a stereo camera. A stereo camera is a type of camera with two or more lenses with a separate image sensor or film frame for each lens. This allows the camera to simulate human binocular vision, and therefore gives it the ability to capture three-dimensional images, a process known as stereo photography.

[0047] In yet another embodiment, the system has a plurality of sensors that comprise a ranging sensor. A ranging sensor requires no physical contact with the object being detected. This type of sensor allows a robot to see an obstacle without actually having to come into contact with it.

[0048] In the system described by the present invention, the dust area prioritizing system comprises a plurality of environment data. Also, the dust area prioritizing system determines an appropriate dust area priority based on the plurality of dust area information, determined dust area map, and plurality of environment data and the computing device instructs said plurality of dust mitigation equipment to perform a dust mitigation.

[0049] In this system that is described in the present invention, the planner coordinates with the overall site planner to deconflict the mitigation equipment and the other equipment such as haul trucks.

[0050] Areas to be treated include haul roads, access roads, stock piles, and open areas. Watering road sis the most common method used for haul road dust control. Surfactants or wetting agents can be added to the water to extend its life as a dust control agent. Slat solutions are commonly mixed with water and used for haul road dust control. Petroleuyjm resins are generally engineered products or byproducts of lubrication oil manufacturing. Polymers include acrylics and vineyls, which are chemical additives, mixed with water to form a diluted solution, then applied to the road surface topically. Adhesives are compounds, solutions, formulas, etc. that are mixed with the soil surface to form a new road surface.