Automation of self-lifting forklift

Techniques are described for facilitating automation of a self-lifting forklift. According to one or more embodiments, a system is provided that can be located on or within a forklift. The system can comprise a lifting system that provides for vertically lifting or lowering the forklift, a power supply, a memory that stores computer readable and executable components, and a processor that executes the computer readable and executable components stored in the memory. The processor can be operably couple to: a plurality of sensors that sense conditions associated with the forklift, a context component that determines context of the forklift, an analysis component that analyzes information from the plurality of sensors and the context component, and a control component that controls the forklift based on an output from the analysis component, wherein the control includes automatically lifting or lowering of the forklift.

TECHNICAL FIELD

Embodiments disclosed and claimed herein relate to techniques that facilitate automation of a self-lifting forklift.

BACKGROUND

Forklifts can lift, transport, load and unload heavy materials and are thus essential to any business or industry associated with the transportation of freight. A forklift typically comprises a mast, a carriage and forks among other components. The mast is the part of the forklift that lifts and lowers a load of materials. Forks are long extensions (like arms) that are attached to the carriage which mounts the forks to the mast and serves as a support structure for the forklift. Materials to be transported or loaded are typically placed on a pallet which supports the load and can be lifted and transported after inserting the forks into the pallet. Forklifts are typically equipped with wheels to enable transportation of the pallet and load. Some forklifts are propelled manually by an operator pushing or pulling for the forklift. Others are self-propelled by a motor and driven by an operator. While such features make conventional forklifts very useful, additional tools or devices are required depending on the circumstances. For example, a standard forklift can load a large truck through the back door of the truck's cargo area and transport pallets deep into the truck's cargo area if the truck is positioned next to a loading dock, thus leveling the surface of the loading dock and the bed of the truck's cargo area. If a truck is not positioned next to a loading dock and is not equipped with a lift gate, then the forklift can be used to lift the pallet and then unload it onto the truck, but the forklift cannot transport the pallet within the truck's cargo area. In this example, another device such as a hand pallet jack is required to transport the pallet within the cargo area of the truck to another location within the cargo area away from the door.

The need for two devices to load and then position a pallet of materials within the cargo bay of a truck in this example is removed in some cases by using a self-lifting forklift. A self-lifting forklift can effectively “climb” into the bed of a truck or other elevated surface. Thus, a self-lifting forklift can lift, transport, load and unload pallets with materials like a conventional forklift while also elevating itself to a height of a load placed at an elevated position, like a lift gate. More particularly, as forks of the self-lifting forklift position a load to an elevated plane, the forks are lowered to the elevated plane to serve as a supporting base. The forks of the self-lifting forklift are suitably counterbalanced for weight then to allow it to lift itself up through a vertical train so that the entire forklift can be relocated at the elevated plane. At this point the forklift can now be used to transport the load within the elevated plane, such as the bed of a truck's cargo area, thus providing the ability to accomplish this and other tasks without a second device.

By eliminating the need for a second device, self-lifting forklifts can be useful in many use cases requiring lifting, transporting, loading and unloading materials. However, other than a powered system that provides for vertically lifting or lowering the forklift, conventional self-lifting forklifts such as described in EP0553086B1 require manual operation by a human operator. For example, when operating the motorized system to lift the forks carrying a pallet, the operator must align the lifted pallet to a position just above the truck bed using the lifting controls and determining the ideal alignment position of the pallet with respect to the truck bed based on the operator's eyesight. This process can be slow and tedious as the operator will often have to lower and raise the forks several times to find a suitable position, oftentimes because the load that the forklift is carrying can obscure the operator's vision. Conventional self-lifting forklifts cannot determine weight of a pallet and materials as compared to safety guidelines for the weight of loads associated with the forklift. Also, conventional self-lifting forklifts are not self-propelled, so an operator must push and pull the forklift in order to move and position it. In the freight delivery business, speed, efficiency and safety are the most important considerations. The advantages of a self-lifting forklift can be improved significantly through automation.

SUMMARY

In one or more embodiments described herein, devices, systems, computer-implemented methods, apparatus and/or computer program products facilitate automation of a self-lifting forklift. In accordance with an embodiment, a system can be located on or within a forklift. The system can comprise a lifting system that provides for vertically lifting or lowering the forklift, a power supply, a memory that stores computer readable and executable components, and a processor that executes the computer readable and executable components stored in the memory. The processor can be operably couple to: a plurality of sensors that sense conditions associated with the forklift, a context component that determines context of the forklift, an analysis component that analyzes information from the plurality of sensors and the context component, and a control component that controls the forklift based on an output from the analysis component, wherein the control includes automatically lifting or lowering of the forklift.

In some implementations, the system further comprises a drive train for self-propelling the forklift.

In some embodiments, elements described in connection with the disclosed systems can be embodied in different forms such as a computer-implemented method, a computer program product, or another form.

DETAILED DESCRIPTION

A self-lifting forklift provides certain advantages over a conventional forklift. A self-lifting forklift can effectively “climb” into the bed of a truck or other elevated surface. Thus, a self-lifting forklift can lift, transport, load and unload pallets with materials like a conventional forklift while also elevating itself to a height of a load placed at an elevated position. More particularly, as forks of the self-lifting forklift position a load to an elevated plane, the forks are lowered to the elevated plane to serve as a supporting base. The forks of the self-lifting forklift are suitably counterbalanced for weight then lifts itself up through a vertical train so that the entire forklift can be relocated at the elevated plane. At this point the forklift can now be used to transport the load within the elevated plane, such as the bed of a truck's cargo area, thus providing the ability to accomplish this and other tasks without a second device.

Self-lifting forklifts can be useful in many use cases requiring lifting, transporting, loading and unloading materials by eliminating the need for a second device such as a lift gate to elevate the load or a hand pallet jack on the bed of a truck after a conventional forklift has loaded a pallet onto the truck bed. However, other than a powered system that provides for vertically lifting or lowering the forklift, conventional self-lifting forklifts require manual operation by a human operator. For example, when operating the motorized system to lift the forks carrying a pallet, the operator must align the lifted pallet to a position just above the truck bed using the lifting controls and determining the ideal alignment position of the pallet with respect to the truck bed based on the operator's eyesight. This process can be slow and tedious as the operator will often have to lower and raise the forks several times to find a suitable position, oftentimes because the load that the forklift is carrying can obscure the operator's vision. Conventional self-lifting forklifts cannot determine weight of a pallet and materials as compared to safety guidelines for the weight of loads associated with the forklift. Also, conventional self-lifting forklifts are not self-propelled, so an operator must push and pull the forklift in order to move and position the forklift. In the freight delivery business, speed, efficiency and safety are the most important considerations. The advantages of a self-lifting forklift can be improved significantly through automation.

In one or more embodiments described herein, systems, computer-implemented methods, and/or computer program products that facilitate automation of a self-lifting forklift are described. By automating one or more functions of a self-lifting forklift, factors such as speed, efficiency and safety can be improved significantly.

Turning now to the drawings,FIG.1illustrates a block diagram of an example, non-limiting system100that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein.

In accordance with an embodiment, the system100can be located on or within a forklift. More particularly, the system100can be embedded within the housing of the forklift or distributed in part within the forklift and externally (e.g., in other equipment, network, or cloud for example). The system can comprise a lifting system108that provides for vertically lifting or lowering the forklift, a power supply110, a memory104that stores computer readable and executable components, and a processor102that executes the computer readable and executable components stored in the memory. The processor102can be operably coupled to: a plurality of sensors112that sense conditions associated with the forklift, a context component114that determines context of the forklift, an analysis component116that analyzes information from the plurality of sensors and the context component, and a control component118that controls the forklift based on an output from the analysis component, wherein the control includes automatically lifting or lowering of the forklift.

The system100can include a bus106that can provide for interconnection of various components of the system100. It is to be appreciated that in other embodiments one or more system components can communicate wirelessly with other components, through a direct wired connection or integrated on a chipset.

In certain embodiments, a communications component can provide for transmitting and receiving information (e.g., through one or more internal or external networks120(wired or wireless networks)).

In certain embodiments, the system100can include a lifting system108that provides for vertically lifting or lowering the forklift. For example, the lifting system can include one or more of: a hydraulic system, a motorized rail system, a linear motor system, a ball and screw system and the like for vertically lifting or lowering the forklift.

In an embodiment, the power supply110can utilize a 480V charger or a 120V charger or any suitable power source.

In an embodiment, batteries and the power supply110are configured for hot-swapping of batteries.

In an embodiment, the power supply110can include a mechanical attachment to a vehicle for transport and charging.

In an embodiment, the power supply110can enable the forklift to scavenge energy and self-charge while lowering a load by the lifting system108.

In certain embodiments, the system100can include a plurality of sensors112that sense conditions associated with the forklift. For example, the sensors112can comprise one or more sensors that sense ambient conditions associated with exterior conditions of the forklift (e.g., sensors that detect temperature, pressure, light, image, humidity, pollution, odors, chemicals, smoke, draft, moisture, air quality, particulate, accelerometers, vibration, noise, tone, weight, relative location of other objects, etc.). For example, the sensors112can collect information associated with the position of the forklift's forks relative to the bed of a truck where a pallet will be placed. The sensors112can also comprise one or more sensors that that can collect information regarding one or more internal components of the forklift (e.g., fuel level, battery charge, condition of brakes, etc.). In another example, the sensors112can comprise one or more sensors that collect information associated with one or more operators of the forklift. The sensors112can also comprise one or more sensors that can collect information regarding associated equipment such as a vehicle, pickup or delivery location or other forklifts.

In an embodiment, the sensors112can also comprise a global positioning system (GPS) component to facilitate location identification, forklift location determination or guidance.

In an embodiment, the sensors112can also comprise one or more sensors for determining curves, changes in slope or incline.

In an embodiment, the sensors112can also comprise one or more sensors such as machine vision to identify terrain and surface conditions. For example, the sensors112can identify when a concrete surface ends and a gravel area begins. In another example, the sensors112can identify potholes or cracks in a surface that can impede or disrupt movement of the forklift.

In certain embodiments, the context component114can determine context of a forklift. Context of a forklift can include a wide variety of attributes associated with the forklift and the intended use of the forklift at a given time, such as location, time of day, day of the week, calendar date, loading and delivery schedules, identify of forklift operator, status of loading and delivery projects and the like. Context of a forklift can also include extrinsic data that can affect intended use of a forklift at a given time such as weather, traffic, inventory, delivery, loading or unloading delays within a supply chain and the like. For example, the context component114can determine or infer context information such as type of load, type of vehicle transporting the load, pallet type, weight, weather, ground conditions, operator skill or experience, height of load, height of forklift, location of the load relative to other objects, etc. Likewise, context information regarding destination of the load and/or vehicle, and/or regarding operational information about the forklift, vehicle and/or pickup or delivery location can be collected and provided to the system100for analysis in connection with regulating forklift operation or control.

The context component114can, for example, obtain context information from many different sources e.g., an operator or occupant cell phone, calendar, email, appliances, third parties, a vehicle, operating environment, the forklift, etc. In one example, the context component114can rely on external systems such as ERP systems, ecommerce platforms, package or freight delivery systems, warehouse schedules, inventory planning systems and the like.

In certain embodiments, the context component114can log data associated with identity of one or more operators of a forklift. The context component114can, for example, identify and authenticate an operator engaging with the forklift utilizing a variety of sources, e.g., via facial recognition, biometrics, voice recognition, iris recognition, cell phone, keys, or any other suitable means for identification and authentication. In another example, the context component114can utilize employment records or other operator records.

In certain embodiments, the analysis component116can analyze information from the plurality of sensors112and the context component114. For example, the analysis component116can analyze various operational steps required to complete a task or series of tasks utilizing the forklift and performs a utility-based analysis that weighs costs versus benefits associated with respective operational options relative to the required task or tasks. In one example, the analysis component116can classify operational options as ideal options, satisfactory options, problematic options or unsafe or prohibited options. In one example, if a required task comprises transporting a pallet with a load to a flatbed truck, the analysis component116can determine the range of ideal placements of the forklift relative to the rear of the truck before lifting the pallet with the forklift. Likewise, the analysis component116can determine the range of satisfactory placements, problematic placements or unsafe or prohibited placements. Next, as the forklift begins to lift the pallet and the load, the analysis component116can determine the range of ideal placements of the pallet relative to the bed of the truck. Likewise, the analysis component116can determine the range of satisfactory placements, problematic placements or unsafe or prohibited placements such as lifting the pallet too high or not high enough. In these examples, the determination of the analysis component116can be affected by other factors such as weight of the load, weather, surface conditions, delivery vehicle dimensions, surface incline and the like. For example, the analysis component116can determine that a particular delivery cannot or should not be made due to an assessment of surface conditions (e.g., too soft, too muddy, too icy, etc.).

In another example, the analysis component116can classify route options associated with the route between the pickup spot for a pallet and the loading spot for a pallet, taking into account a variety of factors such as surface conditions, obstacles, inclines, weather, delivery time, delivery priority and the like.

In another example, the analysis component116can determine if the weight of a load is suitable for the forklift, the likely delivery route or the delivery vehicle.

In another example, a utility-based analysis can also be employed where the costs of taking a certain action are weighed against the benefits. For example, if floor conditions are not optimal as determined by the analysis component116based upon data collected by the sensors112and the context component114, the analysis component116may determine or infer that the probability and cost of an accident occurring outweighs the benefit of moving the load over the sub-optimal floor condition.

In an embodiment, the analysis component116can build and store in memory104forklift operator profiles. An employee of a company that owns a forklift is commonly a frequent user of the forklift, and the analysis component116can build a specific model for the operator as well as respective models for other frequent operators as well as types of forklifts. Upon identification by the context component114of an operator engaging with the forklift, the analysis component116can access specific profiles for each operator of the forklift to generate determinations or inferences regarding operator use and generating recommendations to the control component118to adjust the forklift (e.g., display, height, position, etc.) to achieve suitable configuration for operator engagement with the forklift. The context component114can log data associated with an operator's operation of the forklift and similar forklifts to continuously update the operator profile utilized by the analysis component116. It is to be appreciated that when multiple operators are using the forklift, their respective profiles may conflict in certain aspects. The analysis component116can utilize the respective profiles and specific operator and forklift models to achieve a happy medium that achieves configuration levels suitable for most or all operators.

In an embodiment, the analysis component116can perform self-diagnosis of the forklift and the system100, schedule maintenance, change battery, send notifications or alerts, etc.

In certain embodiments, the control component118can control the forklift based on an output from the analysis component116, wherein the control includes automatically lifting or lowering of the forklift. For example, the control component118can be configured to enable a human operator of the forklift to make certain control and operational decisions associated with the various components of the forklift. Likewise, the control component118can be configured to control certain components automatically based upon output by the analysis component116.

In one example, the control component118can provide an alert to the operator of the forklift when operational decisions can be unsafe or create a problem. Likewise, the control component118can stop or prevent prohibited actions. For example, the control component118can prevent the unloading of a pallet if the forklift is placed too far from the intended unloading spot.

In another example, the control component118can regulate one or more forklift components (e.g., hydraulics, brakes, motor, power, controls, sensors112(including both environmental and those relating to the forklift and/or load), machine vision, cameras, accelerometers, fluids, displays, interfaces, etc.) based on output from the analysis component116to facilitate achieving suitable operation and control of the forklift. Also, the sensors112and context component114can continually collect data that is analyzed by the analysis component116, which will generate determinations or inferences regarding forklift operation or control. The control component118can continually adjust forklift or other equipment conditions or settings to maintain desired operation of the forklift or ancillary equipment. The system100is adaptive and can employ closed or open-looped systems to facilitate maintaining forklift operation or control even as conditions of the forklift operation or control change.

In an embodiment, the control component can activate brakes, e.g., to prevent rolling, tipping, etc., or lock wheels of the forklift.

In an embodiment, the control component118can have preset configurations for engagement of the forklift with various types of other equipment (e.g., vehicle type, pallet type, object type (e.g., beer kegs, chemical drums)). For example, the control component118can have a preset configuration for ideal lift points for the forklift corresponding to various types of trucks and vehicles, thus eliminating the need for the operator of the forklift to visually align the pallet during the lifting and loading process.

In an embodiment, the forklift can change out wheels to match wheel types to planned use of the forklift.

In an embodiment, the forklift is ruggedized (e.g., weather proofed, large tires, greater lift capacity, hi-capacity batteries, etc.) for military or outdoor applications and the like.

In an embodiment, the forklift comprises tracks instead of or in combination with wheels.

In an embodiment, forks can be swappable, fast swappable, made of different materials (e.g., fiberglass, carbon fiber, steel, iron, composites).

In an embodiment, width of the forks can be adjustable, or the forks can be of alternative configuration, e.g., semi-circular forks for beer barrels or chemical drums.

In an embodiment, the forklift can pick up or drop off loads on an incline, e.g., tilting forks (forward or backwards). The forklift can also determine if the load is appropriately placed on the forks, e.g. the load center is not too far forward so that it could tip.

In an embodiment, the forklift can spin on an axis, allowing for use within confined areas, such as delivery vehicles or narrowly spaced warehouse racks.

FIG.2illustrates a block diagram of another example, non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity. In certain embodiments, the system200includes a drive train202(and associated mechanical, electrical or electro-mechanical components, hardware, software and the like) for self-propelling the forklift. For example, the drive train202can utilize systems that provide for autonomous movement of vehicles, carts, robots, drones or the like.

In an embodiment, the forklift is equipped with machine vision to allow for self-navigation and engagement or avoidance of objects. For example, the machine vision can facilitate the forklift self-navigating as well as identifying a load to engage with. The machine vision can facilitate the forklift self-orienting to position forks to insert into pallets, or beneath or around a load and lift, lower and position a palletized or un-palletized load. The machine vision can also enable the forklift to avoid poor surface condition, obstructions and people in order to improve safety.

In another embodiment, cloud-based monitoring and control of the forklift is provided to facilitate remote operation and control of the forklift by a human operator or fully autonomous operation and control of the forklift.

In an embodiment, a fully autonomous or remote-controlled forklift can enter into hazardous areas to move loads and avoid humans from being exposed to the hazardous conditions (e.g., fire, smoke, chemicals, bombs, etc.).

FIG.3illustrates a block diagram of another example, non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity. In certain embodiments, the system300includes an interactive display component302that can visually represent control of the forklift by the control component118. For example, the interactive display component302can visually display operational controls that enable an operator of the forklift to control operations such as lifting or lowering the forklift and propelling the forklift. In one example, the interactive display component302can visually display classifications or recommendations generated by the analysis component116associated with one or more control operations. For example, the interactive display component302can visually display ideal placement of the forklift or a lifted pallet in relation to the bed of a truck when unloading a pallet. In another example, the interactive display component302can visually display warnings of dangerous positioning of the forklift.

In another example, the interactive display component302can visually display the ideal path for the operator of the forklift to follow to a delivery point and can identify potential obstructions or other factors that affect a planned route. In another example, the interactive display component302can visually display ideal load placements within a truck to ensure that all pallets for a particular delivery can fit in the truck bed.

In an embodiment, if the analysis component116determines or infers that an operator of the forklift is fatigued or drowsy, the interactive display component302can provide a notification to the operator to not use the forklift and take a break or increase brightness of the display to increase level of alertness of the operator.

In an embodiment, the interactive display component302can comprise a remote-control device that communicates with and controls system300and one or more forklifts through the wireless network120.

In certain embodiments, the interactive display component302can display visualizations utilizing an augmented reality component or virtual reality component. In one example, the interactive display component302can display visualizations utilizing an augmented reality component contained in glasses worn by an operator of a forklift in order to overlay text, color or images onto the operator's field of vision. For example, the interactive display component302can overlay arrows onto the ground indicating the route to a delivery point. In another example, obstructions such as potholes or cracks in the pavement can be highlighted in red to alert the operator. In another example, the interactive display component302can display visualizations utilizing a virtual reality component contained in a headset worn by an operator of the forklift that simulates the entire field of vision that the operator would see from the perspective of being near the forklift. In this example, the virtual reality component can enable remote operation of the forklift. For example, the virtual reality component can simulate the entire field of vision that an operator would see if the operator was near the forklift, including factors such as space, distance, objects and the like. In addition, the virtual reality component can enhance this view by utilizing overlaid text, color or images to convey useful information to the operator wearing a virtual reality headset. For example, text, color or images can be utilized to convey that an operating surface is wet and possibly slippery, or that the surface inclines or declines in certain areas.

FIGS.4-10illustrate a self-lifting forklift that can incorporate non-limiting system100(or interchangeably200or300) which can be embedded with housing of the forklift or distributed in part within the forklift and externally (e.g., in other equipment, network, or cloud for example).

FIG.4illustrates another example of a non-limiting system100that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.FIG.4depicts a self-lifting forklift400with a pallet402on its forks404. The support legs406provide support. The forklift400can lift and position the pallet402to a desired location, e.g., the top of the flatbed408. The flatbed408can represent any surface on which the pallet402can be loaded by the forklift400(e.g., the bed of a truck, the floor of a van, or a shelf in a storage warehouse for example). In this example, the forklift400has been positioned by the system100(or200or300) immediately in front of the flatbed408to enable loading of the pallet402onto the flatbed408.

FIG.5illustrates another example of a non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.FIG.5illustrates the forklift400being controlled by the system100(or200or300) to lift the forks404, which lift the pallet402to an elevation coincident with the flatbed408. The support legs406provide support as the pallet402is lifted.

FIG.6illustrates another example of a non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.FIG.6illustrates the forklift400being controlled by the system100(or200or300) to move the forklift400as well as lifted pallet402towards the flatbed408so that the pallet402can be placed on the surface of the flatbed406. The support legs406remain in position extending out from the front of the forklift400.

FIG.7illustrates another example of a non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.FIG.7illustrates the forklift400being controlled by the system100(or200or300) to place the pallet402on the flatbed408and to prepare itself for self-lifting by moving the support legs406from extending out from the front of the forklift400to extending out from the rear of the forklift400. The support legs406act as counterweights or stabilizers in this new position to enable self-lifting of the forklift400.

FIG.8illustrates another example of a non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.FIG.8illustrates the forklift400being controlled by the system100(or200or300) to self-lift to an elevation coincident with the surface of the flatbed408. As discussed herein the forklift400employs a lifting system108to lift itself to a desired elevation.

FIG.9illustrates another example of a non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.FIG.9illustrates the forklift400being controlled by the system100(or200or300) to be positioned at a desired elevation. The support legs406are moved back to their original position in front of the forklift400and under the pallet402.

FIG.10illustrates another example of a non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.FIG.10illustrates the forklift400being controlled by the system100(or200or300) to be self-positioned at a desired position on the flatbed408.

FIG.11illustrates a block diagram of another example, non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity. In certain embodiments, the system1100includes a crowdsourcing component1102that can facilitate the analysis of information by the analysis component116from the plurality of sensors112and the context component114. For example, the crowdsourcing component1102can collect information shared by other forklifts regarding surface conditions at or near delivery sites, pedestrian or vehicle traffic, weather information and the like. In one example, the crowdsourcing component1102associated with weather conditions that are causing similar forklifts to lose traction at a loading or delivery site.

In another example, the crowdsourcing component1102can collect information shared by other forklifts regarding how certain forklift models handle different load weights under various weather, surface or incline positions. Likewise, the crowdsourcing component1102can collect information shared by other forklifts regarding wear and tear of certain forklift models.

In another example, the crowdsourcing component1102can collect real-time information from other forklifts, delivery vehicles, loading or unloading locations that can affect delivery preferred delivery times as determined by the analysis component116.

FIG.12illustrates a block diagram of another example, non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity. In certain embodiments, the system1200includes an artificial intelligence component1202that utilizes machine learning to facilitate the analyzing of information by the analysis component116from the plurality of sensors112and the context component114. For example, the artificial intelligence component1202can detect patterns associated with how the forklift or similar forklifts perform under various conditions such as load weight, inclines/declines, weather conditions, operator error, wear and tear and the like. For example, the weight guidelines utilized by the analysis component116to determine weight or incline/decline limits for pallet loads can be adjusted if the forklift experiences problems at certain weight or incline/decline levels. In another example, the artificial intelligence component1202can detect patterns associated with operator error in certain situations, causing the analysis component116to adjust recommendations associated with certain operational decisions.

In another example, the artificial intelligence component1202can utilize data collected by the crowdsourcing component1102that certain components of the forklift such as the braking component will require maintenance much sooner or much later than expected due to actual usage data, thus adjusting maintenance recommendations issued by the analysis component116.

In this regard, the artificial intelligence component1202can perform classifications, correlations, inferences and/or expressions associated with principles of artificial intelligence. For instance, the artificial intelligence component1202can employ an automatic classification system and/or an automatic classification. In one example, the artificial intelligence component1202can employ a probabilistic and/or statistical-based analysis (e.g., factoring into the analysis utilities and costs) to learn and/or generate inferences. The artificial intelligence component1202can employ any suitable machine-learning based techniques, statistical-based techniques and/or probabilistic-based techniques. For example, the artificial intelligence component1202can employ expert systems, fuzzy logic, SVMs, Hidden Markov Models (HMMs), greedy search algorithms, rule-based systems, Bayesian models (e.g., Bayesian networks), neural networks, other non-linear training techniques, data fusion, utility-based analytical systems, systems employing Bayesian models, etc. In another aspect, the artificial intelligence component1202can perform a set of machine learning computations. For example, the artificial intelligence component1202can perform a set of clustering machine learning computations, a set of logistic regression machine learning computations, a set of decision tree machine learning computations, a set of random forest machine learning computations, a set of regression tree machine learning computations, a set of least square machine learning computations, a set of instance-based machine learning computations, a set of regression machine learning computations, a set of support vector regression machine learning computations, a set of k-means machine learning computations, a set of spectral clustering machine learning computations, a set of rule learning machine learning computations, a set of Bayesian machine learning computations, a set of deep Boltzmann machine computations, a set of deep belief network computations, and/or a set of different machine learning computations.

FIG.13illustrates a block diagram of another example, non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity. In certain embodiments, the system1300includes an audio component1302that facilitates control of the forklift by the control component118utilizing voice commands. For example, an operator of the forklift can control operations such as lifting or lowering the forklift and propelling the forklift by using voice commands. The audio component1302can employ natural language processing to enable the implementation of voice commands. The control component118can provide alerts to the operator if a voice command is unclear and cannot be executed. In another example, profiles of operators compiled by the analysis component116can include voice profiles corresponding to operators in order to improve the effectiveness of voice commands given by frequent users of the forklift.

FIG.14illustrates a block diagram of another example, non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity. In certain embodiments, the system1400includes an integration component1402that integrates the system1400with other devices and systems. For example, the integration component1402can enable the forklift to integrate with and communicate with other forklifts, trucks, smart pallets, vans, trucks and other delivery vehicles, carts, robots, drones, warehouse loading docks, garage doors, loading docks of businesses or residences receiving goods and the like. Such communication can enable coordination of factors such as availability of packages for pickup, pickup and delivery times, load capacity within delivery vehicles, matching pallet and load with suitable forklift, etc.

In an embodiment, the integration component1402can enable the forklift to communicate with smart pallets that are equipped with sensors and communication components so that the forklift and pallets can work in tandem in connection with moving a palletized or un-palletized load or loading or unloading the pallet. For example, the smart pallet can broadcast its location and orientation to the forklift. In another embodiment, the pallet can broadcast weight of its load or even details of the load to the forklift. Likewise, the integration component1402can enable the forklift to communicate with other equipment in similar fashion to facilitate autonomous or semi-autonomous operation of the forklift in connection with load transport.

In an embodiment, the integration component1402can enable the forklift to communicate with a retrofit rail pallet moving system that can be placed in a shipping container to facilitate moving pallets within the container. In an embodiment, a conveyor system is used to allow for the pallets to be moved along the conveyor. The conveyor can be powered in an embodiment. In another embodiment, a linear motor system can be used to move the pallets. In another embodiment, a rail or track system with positionable and/or telescopic forks can be employed to move pallets within the container. This retrofit system can communicate and interact with the forklift.

In an embodiment, the integration component1402can enable the forklift to communicate with a loading dock. In an embodiment, the control component118can employ a queuing system to facilitate task management (e.g., pre-signals to dock, charging, scheduling, workload, load balancing of work, weight determination, knowing which truck to unload first).

In an embodiment, the forklift can interact with other forklifts. For example, a large or heavy load may require more than one forklift for transportation. In this example, one or more forklifts can coordinate to transport the load. In cases of uneven weight distribution within the load, each forklift's sensors can determine weight distribution and adjust accordingly as the load is transported.

In an embodiment, the forklift can interact with a stacker.

In an embodiment, the forklift can communicate with a garage door opener to facilitate entering and exiting of a garage and delivery of packages.

In an embodiment, the forklift can communicate with a lift gate (safety—knowing whether it's safely engaged) for safe hand-off.

FIG.15illustrates yet another example of a non-limiting system that facilitates automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.FIG.15depicts an example1500of system1400that enables the self-lifting forklift1502to integrate with and communicate with other devices and systems. This example depicts the forklift1502integrated with a smart pallet1504, a flatbed truck1506, a conventional forklift1508, another self-lifting forklift1510, a van1512, a warehouse1514, a large truck1516and a garage door of a residence1518.FIG.15illustrates how a fully automated and fully autonomous embodiment of the self-lifting forklift1502can complete its task without requiring direct human involvement. For example, for an order to be delivered to a residence, the self-lifting forklift1502can communicate with the smart pallet1504, the forklift1508and/or the warehouse1512to coordinate pickup time and location. The self-lifting forklift1502can coordinate with the flatbed truck1506, the van1510or the large truck1514for transportation to the pickup location at the pickup time. The self-lifting forklift1502with autonomous capability does not require direct human operation to lower itself from the delivery vehicle and then transport itself to the location of the delivery item. The self-lifting forklift1502can then retrieve the pallet1504with the delivery item and then load it onto the delivery vehicle which can transport the self-lifting forklift1502with the pallet. At this point the self-lifting forklift1502can communicate with the garage door of the residence1518where the package is scheduled to be delivered. Upon arrival at the residence, the self-lifting forklift1502can lower itself with the pallet1504onto the pavement and then deliver the pallet1504into the garage by coordinating with the garage door1518which can authenticate the self-lifting forklift1502and the pallet1504and permit entry. In another example, the self-lifting forklift1502can communicate with one or more other self-lifting forklifts1510to coordinate and complete loading, transportation, delivery and unloading tasks.

FIG.16illustrates a flow diagram of an example of a method to facilitate automation of a self-lifting forklift in accordance with one or more embodiments described herein. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.1602represents a first act that includes sensing conditions associated with a forklift (e.g., via the sensors112). At1604, context of the forklift is determined (e.g., via the context component114). At1606, information associated with conditions and context of the forklift is analyzed (e.g., via the analysis component116). At1608, the forklift is controlled based on analysis of the information analyzed at1604, including automatically lifting or lowering of the forklift (e.g., via the control component118).

In certain embodiments, at1608, the forklift is controlled based on analysis of the information analyzed at1604, including self-propelling the forklift (e.g., via the control component118). In another embodiment, at1608, control of the forklift is visually represented to facilitate control of the forklift.

FIG.17illustrates another basic method flow diagram1700of functional acts within various embodiments. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity. The method to facilitate automation of a self-lifting forklift illustrated inFIG.17can be implemented in the system100ofFIG.1. As such, reference is to be made to the example of FIG.1in the following discussion of the example ofFIG.17.

Thus, in the example ofFIG.17, a sequence to facilitate automation of a self-lifting forklift1700is outlined. The sequence begins at1702where a pallet with a load to be loaded and then transported to a delivery vehicle by the forklift for delivery is identified. At1704, the pallet with the load is loaded onto the forklift. At1706, it is determined if the weight and size of the load are suitable for the forklift and the delivery vehicle. For example, the weight of the load may exceed the safety limit of the forklift, or the size of the load may be too large for the delivery vehicle. If either the weight or size of the load is not suitable for the forklift or the delivery vehicle1708, then remediation is required. For example, the load on the pallet can be separated and placed on two pallets. Once action is taken1710to remediate, step1706is repeated. If the weight and size of the load are both suitable1712, then at1714it is determined if the environment is suitable for the forklift to transport the pallet and the load to the delivery vehicle. For example, the condition of the surface of the path for transportation may be too muddy or too slippery, or there may be obstructions. If the environment is not suitable1716, remediation is required. In one example, an alternate path to the delivery vehicle can be selected. In another example, transportation to the delivery vehicle can be delayed. Once action is taken1718to remediate, step1714is repeated. If the environment is suitable1720, then the pallet and load is transported to the delivery vehicle and the forklift is positioned in a suitable location to load the pallet onto the delivery vehicle1722. At1724, the pallet is loaded onto the delivery vehicle and the forklift is lifted onto the delivery vehicle.

In order to provide a context for the various aspects of the disclosed subject matter,FIG.18as well as the following discussion are intended to provide a general description of a suitable environment in which the various aspects of the disclosed subject matter can be implemented.FIG.18illustrates a block diagram of an example, non-limiting operating environment in which one or more embodiments described herein can be facilitated. Repetitive description of like elements employed in other embodiments described herein is omitted for sake of brevity.

With reference toFIG.18, a suitable operating environment1800for implementing various aspects of this disclosure can also include a computer1812. The computer1812can also include a processing unit1814, a system memory1816, and a system bus1818. The system bus1818couples system components including, but not limited to, the system memory1816to the processing unit1814. The processing unit1814can be any of various available processors. Dual microprocessors and other multiprocessor architectures also can be employed as the processing unit1814. The system bus1818can be any of several types of bus structure(s) including the memory bus or memory controller, a peripheral bus or external bus, and/or a local bus using any variety of available bus architectures including, but not limited to, Industrial Standard Architecture (ISA), Micro-Channel Architecture (MSA), Extended ISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component Interconnect (PCI), Card Bus, Universal Serial Bus (USB), Advanced Graphics Port (AGP), Firewire (IEEE 1394), and Small Computer Systems Interface (SCSI).

The system memory1816can also include volatile memory1820and non-volatile memory1822. The basic input/output system (BIOS), containing the basic routines to transfer information between elements within the computer1812, such as during start-up, is stored in non-volatile memory1822. Computer1812can also include removable/non-removable, volatile/non-volatile computer storage media.FIG.18illustrates, for example, a disk storage1824. Disk storage1824can also include, but is not limited to, devices like a magnetic disk drive, floppy disk drive, tape drive, Jaz drive, Zip drive, LS-100 drive, flash memory card, or memory stick. The disk storage1824also can include storage media separately or in combination with other storage media. To facilitate connection of the disk storage1824to the system bus1818, a removable or non-removable interface is typically used, such as interface1826.FIG.18also depicts software that acts as an intermediary between users and the basic computer resources described in the suitable operating environment1800. Such software can also include, for example, an operating system1828. Operating system1828, which can be stored on disk storage1824, acts to control and allocate resources of the computer1812.

System applications1830take advantage of the management of resources by operating system1828through program modules1832and program data1834, e.g., stored either in system memory1816or on disk storage1824. It is to be appreciated that this disclosure can be implemented with various operating systems or combinations of operating systems. A user enters commands or information into the computer1812through input device(s)1836. Input devices1836include, but are not limited to, a pointing device such as a mouse, trackball, stylus, touch pad, keyboard, microphone, joystick, game pad, satellite dish, scanner, TV tuner card, digital camera, digital video camera, web camera, and the like. These and other input devices connect to the processing unit1814through the system bus1818via interface port(s)1838. Interface port(s)1838include, for example, a serial port, a parallel port, a game port, and a universal serial bus (USB). Output device(s)1840use some of the same type of ports as input device(s)1836. Thus, for example, a USB port can be used to provide input to computer1812, and to output information from computer1812to an output device1840. Output adapter1842is provided to illustrate that there are some output devices1840like monitors, speakers, and printers, among other output devices1840, which require special adapters. The output adapters1842include, by way of illustration and not limitation, video and sound cards that provide a means of connection between the output device1840and the system bus1818. It should be noted that other devices and/or systems of devices provide both input and output capabilities such as remote computer(s)1844.

Computer1812can operate in a networked environment using logical connections to one or more remote computers, such as remote computer(s)1844. The remote computer(s)1844can be a computer, a server, a router, a network PC, a workstation, a microprocessor-based appliance, a peer device or other common network node and the like, and typically can also include many or all of the elements described relative to computer1812. For purposes of brevity, only a memory storage device746is illustrated with remote computer(s)1844. Remote computer(s)1844is logically connected to computer1812through a network interface1848and then physically connected via communication connection1850. Network interface1848encompasses wire and/or wireless communication networks such as local-area networks (LAN), wide-area networks (WAN), cellular networks, etc. LAN technologies include Fiber Distributed Data Interface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet, Token Ring and the like. WAN technologies include, but are not limited to, point-to-point links, circuit switching networks like Integrated Services Digital Networks (ISDN) and variations thereon, packet switching networks, and Digital Subscriber Lines (DSL). Communication connection(s)1850refers to the hardware/software employed to connect the network interface1848to the system bus1818. While communication connection1850is shown for illustrative clarity inside computer1812, it can also be external to computer1812. The hardware/software for connection to the network interface1848can also include, for exemplary purposes only, internal and external technologies such as, modems including regular telephone grade modems, cable modems and DSL modems, ISDN adapters, and Ethernet cards.

Referring now toFIG.19, an illustrative cloud computing environment1950is depicted. As shown, cloud computing environment1950includes one or more cloud computing nodes1910with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone1954A, desktop computer1954B, laptop computer1954C, and/or automobile computer system1954N may communicate. Although not illustrated inFIG.19, cloud computing nodes1910can further comprise a quantum platform (e.g., quantum computer, quantum hardware, quantum software, etc.) with which local computing devices used by cloud consumers can communicate. Nodes1910may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment1950to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices1954A-N shown inFIG.19are intended to be illustrative only and that computing nodes1910and cloud computing environment1950can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser).

Referring now toFIG.20, a set of functional abstraction layers provided by cloud computing environment1950(FIG.19) is shown. It should be understood in advance that the components, layers, and functions shown inFIG.20are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided:

Hardware and software layer2060includes hardware and software components. Examples of hardware components include: mainframes2061; RISC (Reduced Instruction Set Computer) architecture-based servers2062; servers2063; blade servers2064; storage devices2065; and networks and networking components2066. In some embodiments, software components include network application server software2067, quantum platform routing software2068, and/or quantum software (not illustrated inFIG.20).

Virtualization layer2070provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers2071; virtual storage2072; virtual networks2073, including virtual private networks; virtual applications and operating systems2074; and virtual clients2075.

In one example, management layer2080may provide the functions described below. Resource provisioning2081provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing2082provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may include application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal2083provides access to the cloud computing environment for consumers and system administrators. Service level management2084provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment2085provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA.

Workloads layer2090provides examples of functionality for which the cloud computing environment may be utilized. Non-limiting examples of workloads and functions which may be provided from this layer include: mapping and navigation2091; software development and lifecycle management2092; virtual classroom education delivery2093; data analytics processing2094; transaction processing2095; and quantum state preparation software2096.