This invention relates to robot navigation and more particularly to robot navigation management within an environment having a plurality of different areas or zones.
Ordering products over the internet for home delivery is an extremely popular way of shopping. Fulfilling such orders in a timely, accurate and efficient manner is logistically challenging to say the least. Clicking the “check out” button in a virtual shopping cart creates an “order.” The order includes a listing of items that are to be shipped to a particular address. The process of “fulfillment” involves physically taking or “picking” these items from a large warehouse, packing them, and shipping them to the designated address. An important goal of the order-fulfillment process is thus to ship as many items in as short a time as possible.
The order-fulfillment process typically takes place in a large warehouse that contains many products, including those listed in the order. Among the tasks of order fulfillment is therefore that of traversing the warehouse to find and collect the various items listed in an order. In addition, the products that will ultimately be shipped first need to be received in the warehouse and stored or “placed” in storage bins in an orderly fashion throughout the warehouse so they can be readily retrieved for shipping.
In a large warehouse, the goods that are being delivered and ordered can be stored in the warehouse very far apart from each other and dispersed among a great number of other goods. With an order-fulfillment process using only human operators to place and pick the goods requires the operators to do a great deal of walking and can be inefficient and time consuming. Since the efficiency of the fulfillment process is a function of the number of items shipped per unit time, increasing time reduces efficiency.
In order to increase efficiency, robots may be used to perform functions of humans or they may be used to supplement the humans' activities. For example, robots may be assigned to “place” a number of items in various locations dispersed throughout the warehouse or to “pick” items from various locations for packing and shipping. The picking and placing may be done by the robot alone or with the assistance of human operators. For example, in the case of a pick operation, the human operator would pick items from shelves and place them on the robots or, in the case of a place operation, the human operator would pick items from the robot and place them on the shelves.
Some warehouses or other environments are be divided into a variety of different areas. For example, some products may require temperature control and are therefore located in a temperature-controlled area, such as a freezer. Some products may require higher security and are therefore placed in an area separated from other products by a barrier. Some environments have areas located at different elevations, which may be accessed via a sloped floor or an elevator. Some different areas are separated by physical barriers such as walls, while other different areas may have no physical barrier separating them. Navigating between such areas can lead to inefficient routing or to traffic congestion between a plurality of robots or between robots and human operators.
Provided herein are methods and systems for robot navigation management in an environment or navigational space having a plurality of zones.
In one aspect, a method for navigating an autonomous robot from a first zone to a second, adjacent zone within an environment is provided. The method includes defining, by a server, the first zone and the second zone within the environment, a threshold along a border between the first and second zones, and a waypoint associated with the threshold; determining for the autonomous robot a route from the first zone to the second zone crossing the threshold, the route including the waypoint; and navigating the robot along the route from the first zone to the second zone, including traversing the waypoint in conjunction with crossing the threshold. In some embodiments, the waypoint is defined by a waypoint pose and the step of determining a route includes determining a route segment to the waypoint pose. The step of traversing the waypoint can include traversing the waypoint pose without pausing at the waypoint pose or pausing at the waypoint pose before crossing the threshold. The waypoint can be spaced a distance from the threshold or located on the border along the threshold.
In some embodiments, the method further comprises defining, by the server, a second waypoint associated with the threshold, the waypoint and the second waypoint located on opposite sides of the threshold. In some embodiments, the border between the two adjacent zones is a physical barrier and the threshold is located at an opening in the physical barrier. In some embodiments, the border between the two adjacent zones is a virtual barrier, and the threshold is a defined location along the virtual barrier. In some embodiments, the method further comprises defining, by the server, a second threshold along the border between the adjacent zones, a second waypoint associated with the second threshold. In some embodiments, the method further comprises defining, by the server, the threshold to permit robot traffic in a first direction, and defining a second threshold along the border between the adjacent zones to permit robot traffic in an opposite direction from the first direction.
In some embodiments, the method further comprises joining, by the robot, a queue of robots waiting to pass threshold. In some embodiments, the method further comprises detecting, by the robot, an obstruction in the threshold with a camera, a laser detector, or a radar detector, or a combination thereof. In some embodiments, each of the zones is a secured area, a temperature controlled area, a warehouse area, or an area having a different elevation from an adjacent area, or a combination thereof.
In a further aspect, a system for navigating an autonomous robot from a first zone to a second, adjacent zone within an environment is provided. The system comprises a server configured to define the first zone and the second zone within the environment, a threshold along a border between the first and second zones, and a waypoint associated with the threshold, an autonomous robot in communication with the server, the robot including a processor and a memory, the memory storing instructions that, when executed by the processor, case the robot to: determine a route from the first zone to the second zone crossing the threshold, the threshold including the waypoint; and navigate the robot along the route from the first zone to the second zone, including traversing the waypoint in conjunction with crossing the threshold. In some embodiments, the waypoint is defined by a waypoint poise and the memory further stores instructions that, when executed by the processor, cause the autonomous robot to determine a route segment to the waypoint pose. In some embodiments, the memory further stores instructions that, when executed by the processor, cause the robot to traverse waypoint pose without pausing at the waypoint pose, or to pause at the waypoint pose before crossing the threshold. In some embodiments, the waypoint is spaced a distance from the threshold or located on the border along the threshold. In some embodiments, the server is configured to define a second waypoint associated with the threshold, the waypoint and the second waypoint located on opposite sides of the threshold.
In some embodiments, the border between the two adjacent zones is a physical barrier and the threshold is located at an opening in the physical barrier. In some embodiments, the border between the two adjacent zones is a virtual barrier, and the threshold is a defined location along the virtual barrier. In some embodiments, the server is configured to define a second threshold along the border between the two adjacent zones, and a second waypoint associated with the second threshold. In some embodiments, the robot navigation server is configured to define the threshold to permit robot traffic in a first direction, and to define a second threshold along the border between the first zone and the second zone to permit robot traffic in an opposite direction from the first direction.
In some embodiments, the memory further stores instructions that, when executed by the processor, cause the autonomous robot to join a queue of robots waiting to pass the threshold. In some embodiments, the memory further stores instructions that, when executed by the processor, cause the autonomous robot to detect an obstruction in the threshold with a camera, a laser detector, or a radar detector, or a combination thereof.
In some embodiments, each of the zones is a secured area, a temperature controlled area, a warehouse area, or an area having a different elevation from an adjacent area, or a combination thereof. In some embodiments, the server further comprises one or more of a warehouse management system, an order-server, a standalone server, a distributed system comprising the memory of at least two of the plurality of robots, or combinations thereof.
These and other features of the invention will be apparent from the following detailed description and the accompanying figures, in which:
The disclosure and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments and examples that are described and/or illustrated in the accompanying drawings and detailed in the following description. It should be noted that the features illustrated in the drawings are not necessarily drawn to scale, and features of one embodiment may be employed with other embodiments as the skilled artisan would recognize, even if not explicitly stated herein. Descriptions of well-known components and processing techniques may be omitted so as to not unnecessarily obscure the embodiments of the disclosure. The examples used herein are intended merely to facilitate an understanding of ways in which the disclosure may be practiced and to further enable those of skill in the art to practice the embodiments of the disclosure. Accordingly, the examples and embodiments herein should not be construed as limiting the scope of the disclosure. Moreover, it is noted that like reference numerals represent similar parts throughout the several views of the drawings.
The invention is directed to robot navigation management. Although not restricted to any particular robot application, one suitable application that the invention may be used in is order fulfillment. The use of robots in this application will be described to provide context for robot navigation management but is not limited to that application.
Referring to
In a preferred embodiment, a robot 18, shown in
Referring again to
Although a robot 18 excels at moving around the warehouse 10, with current robot technology, it is not very good at quickly and efficiently picking items from a shelf and placing them in the tote 44 due to the technical difficulties associated with robotic manipulation of objects. A more efficient way of picking items is to use a local operator 50, which is typically human, to carry out the task of physically removing an ordered item from a shelf 12 and placing it on robot 18, for example, in tote 44. The robot 18 communicates the order to the local operator 50 via the tablet 48 (or laptop/other user input device), which the local operator 50 can read, or by transmitting the order to a handheld device used by the local operator 50.
Upon receiving an order 16 from the order server 14, the robot 18 proceeds to a first warehouse location, e.g. as shown in
Upon reaching the correct location (pose), the robot 18 parks itself in front of a shelf 12 on which the item is stored and waits for a local operator 50 to retrieve the item from the shelf 12 and place it in tote 44. If robot 18 has other items to retrieve it proceeds to those locations. The item(s) retrieved by robot 18 are then delivered to a processing station 100,
It will be understood by those skilled in the art that each robot may be fulfilling one or more orders and each order may consist of one or more items. Typically, some form of route optimization software would be included to increase efficiency, but this is beyond the scope of this invention and is therefore not described herein.
In order to simplify the description of the invention, a single robot 18 and operator 50 are described. However, as is evident from
The baseline navigation approach of this invention, as well as the semantic mapping of a SKU of an item to be retrieved to a fiducial ID/pose associated with a fiducial marker in the warehouse where the item is located, is described in detail below with respect to
Using one or more robots 18, a map of the warehouse 10 must be created and the location of various fiducial markers dispersed throughout the warehouse must be determined. To do this, one or more of the robots 18 as they are navigating the warehouse they are building/updating a map 10a,
Robot 18 utilizes its laser-radar 22 to create map 10a of warehouse 10 as robot 18 travels throughout the space identifying open space 112, walls 114, objects 116, and other static obstacles, such as shelf 12, in the space, based on the reflections it receives as the laser-radar scans the environment.
While constructing the map 10a (or updating it thereafter), one or more robots 18 navigates through warehouse 10 using camera 26 to scan the environment to locate fiducial markers (two-dimensional bar codes) dispersed throughout the warehouse on shelves proximate bins, such as 32 and 34,
By the use of wheel encoders and heading sensors, vector 120, and the robot's position in the warehouse 10 can be determined. Using the captured image of a fiducial marker/two-dimensional barcode and its known size, robot 18 can determine the orientation with respect to and distance from the robot of the fiducial marker/two-dimensional barcode, vector 130. With vectors 120 and 130 known, vector 140, between origin 110 and fiducial marker 30, can be determined. From vector 140 and the determined orientation of the fiducial marker/two-dimensional barcode relative to robot 18, the pose (position and orientation) defined by a quaternion (x, y, z, w) for fiducial marker 30 can be determined.
Flow chart 200,
In look-up table 300, which may be stored in the memory of each robot, there are included for each fiducial marker a fiducial identification, 1, 2, 3, etc., and a pose for the fiducial marker/bar code associated with each fiducial identification. The pose consists of the x,y,z coordinates in the warehouse along with the orientation or the quaternion (x,y,z,ω).
In another look-up Table 400,
The alpha-numeric bin locations are understandable to humans, e.g. operator 50,
The order fulfillment process according to this invention is depicted in flow chart 500,
Continuing to refer to
Item specific information, such as SKU number and bin location, obtained by the warehouse management system 15/order server 14, can be transmitted to tablet 48 on robot 18 so that the operator 50 can be informed of the particular items to be retrieved when the robot arrives at each fiducial marker location.
With the SLAM map and the pose of the fiducial ID's known, robot 18 can readily navigate to any one of the fiducial ID's using various robot navigation techniques. The preferred approach involves setting an initial route to the fiducial marker pose given the knowledge of the open space 112 in the warehouse 10 and the walls 114, shelves (such as shelf 12) and other obstacles 116. As the robot begins to traverse the warehouse using its laser radar 26, it determines if there are any obstacles in its path, either fixed or dynamic, such as other robots 18 and/or operators 50, and iteratively updates its path to the pose of the fiducial marker. The robot re-plans its route about once every 50 milliseconds, constantly searching for the most efficient and effective path while avoiding obstacles.
With the product SKU/fiducial ID to fiducial pose mapping technique combined with the SLAM navigation technique both described herein, robots 18 are able to very efficiently and effectively navigate the warehouse space without having to use more complex navigation approaches typically used which involve grid lines and intermediate fiducial markers to determine location within the warehouse.
With the SLAM map and the pose of the fiducial ID's known, robot 18 can readily navigate to any one of the fiducials using various robot navigation techniques. The preferred approach involves setting an initial route to the fiducial marker pose given the knowledge of the open space 112 in the warehouse 10 and the walls 114, shelves (such as shelf 12) and other obstacles 116. As the robot begins to traverse the warehouse using its laser-radar 22, it determines if there are any obstacles in its path, either fixed or dynamic, such as other robots 18 and/or operators 50, and iteratively updates its path to the pose of the fiducial marker. The robot re-plans its route about once every 50 milliseconds, constantly searching for the most efficient and effective path while avoiding obstacles. Localization of the robot within the warehouse can be achieved, for example, by many-to-many multiresolution scan matching (M3RSM) operating on the SLAM map. M3RSM is described in U.S. Pat. No. 10,386,851, issued Aug. 20, 2019, entitled “MULTI-RESOLUTION SCAN MATCHING WITH EXCLUSION ZONES,” the disclosure of which is incorporated by reference herein. As also described in U.S. Pat. No. 10,429,847, issued Oct. 1, 2019, entitled “DYNAMIC WINDOW APPROACH USING OPTIMAL RECIPROCAL COLLISON AVOIDANCE COST-CRITIC” can be used.
Data processor 620, processing modules 640 and sensor support modules 660 are capable of communicating with any of the components, devices or modules herein shown or described for robot system 600. A transceiver module 670 may be included to transmit and receive data. Transceiver module 670 may transmit and receive data and information to and from a supervisor system or to and from one or other robots. Transmitting and receiving data may include map data, path data, search data, sensor data, location and orientation data, velocity data, and processing module instructions or code, robot parameter and environment settings, and other data necessary to the operation of robot system 600.
In some embodiments, range sensor modules 662 may comprise one or more of a scanning laser, radar, laser range finder, range finder, ultrasonic obstacle detector, a stereo vision system, a monocular vision system, a camera, and an image unit. Range sensor module 662 ma scan an environment around the robot to determine a location of one or more obstacles with respect to the robot. In some embodiments, drive train/wheel encoders 664 comprise one or more sensors for encoding wheel position and an actuator for controlling the positon of one or more wheels (e.g., ground engaging wheels). Robot system 600 may also include a ground speed sensor comprising a speedometer or radar-based sensor r a rotational velocity sensor. The rotational velocity sensor may comprise the combination of an accelerometer and an integrator. The rotational velocity sensor may provide an observed rotational velocity for the data processor 620, or any module thereof.
In some embodiments, sensor support modules 660 may provide translational data, position data, rotation data, level data, inertial data, and heading data, including historical data of instantaneous measures of velocity transition, position, rotation level, heading, and inertial data over time. The translational or rotational velocity may be detected with reference to one or more fixed reference points or stationary objects in the robot environment. Translational velocity may be expressed as an absolute speed in a direction or as a first derivative or robot position versus time. Rotational velocity may be expressed as a speed in angular units or as the first derivative of the angular position versus time. Translational and rotational velocity may be expressed with respect to an origin 0,0 (
In some embodiments, navigation by an autonomous or semi-autonomous robot requires some form of spatial model of the robot's environment. Spatial models are further described in U.S. Pat. No. 10,386,851. Spatial models may be represented by bitmaps, object maps, landmark maps, and other forms of two- and three-dimensional digital representations. A spatial model of a warehouse facility may represent a warehouse and obstacles within such as walls, ceilings, roof supports, windows and doors, shelving and storage bins. Obstacles may be stationary or moving, for example, such as other robots or machinery operating within the warehouse, or relatively fixed but changing, such as temporary partitions, pallets, shelves and bins as warehouse items are stocked, picked and replenished. Spatial models may also represent target locations, such as a shelf or bin marked with a fiducial to which a robot may be directed to perform a task or to a temporary holding location or to the location of a charging station. Spatial models can also include virtual obstacles and objects, such as barriers, threshold crossings, and RFID tunnels.
In some environments, a map may be used by a robot to determine its pose within an environment and to plan and control its movements along a path while avoiding obstacles. Such maps may be “local maps,” representing spatial features in the immediate vicinity of the robot or target location, or “global maps,” representing features on an area or facility encompassing the operating range of one or more robots. Maps may be provided to a robot from an external supervisory system or a robot may construct its map using onboard range finding and location sensors. One or more robots may cooperatively map a shared environment, the resulting map further enhanced as the robots navigate, collect, and share information about the environment.
In some embodiments the supervisory system may comprise a central server performing supervision of a plurality of robots in a manufacturing warehouse or other facility, or the supervisory system may comprise a distributed supervisory system consisting of one or more servers operating within or without the facility either fully remotely or partially without loss of generality in the application of the methods and systems herein described. The supervisory system may include a server or servers having at least a computer processor and a memory for executing a supervisory system and may further include one or more transceivers for communicating information to one or more robots operating in the warehouse or other facility. Supervisory systems may be hosted on computer servers or may be hosted in the cloud and communicating with the local robots via a local transceiver configured to receive and transmit messages to and from the robots and the supervisory system over wired and/or wireless communications media including over the Internet.
One skilled in the art would recognize that robotic mapping for the purposes of the present invention could be performed using methods known in the art without loss of generality. Further discussion of methods for robotic mapping can be found in Sebastian Thrun, “Robotic Mapping: A Survey”, Carnegie-Mellon University, CMU-CS-02-111, February, 2002, which is incorporated herein by reference.
Some navigational spaces or environments, such as a warehouse, can be divided into two or more zones. Such zones can include, for example and without limitation, a secured area for products requiring greater security, a temperature controlled area such as a freezer, an area for a particular type of goods, or an area with a different elevation from an adjacent area. Zones can include, for example, shelves 12 filled with items to be included in an order, as described above. Zones can be free of shelves or other obstacles, for example, to accommodate rapid movement of robots within the environment.
Zones can be demarcated by physical barriers, such as fixed walls or movable partitions. Zones can be demarcated by virtual barriers, in which no physical barrier is present. Physical barriers can include a door or other movable closure therein. Adjacent zones having different elevations can be accessible via a sloped floor or an elevator.
Described herein are systems and methods for robot navigation management in order to enable a robot 18 to navigate an environment divided into two or more zones.
The map also indicates passages or thresholds through the borders, where robots 18 or humans 50 can pass from one zone to an adjacent zone. In the embodiment illustrated in
Thresholds can be defined to allow passage of robots in both directions or in only one direction. For example, the thresholds 932 and 946 are defined to allow passage in both directions, indicated by double-headed arrows. The threshold 952 is defined to allow passage in one direction, from zone 903 into zone 905, and the threshold 948 is defined to allow passage in an opposite direction, from zone 905 into zone 903.
At least one waypoint is associated with each threshold. In some embodiments, two waypoints are associated with each threshold. In some embodiments, a waypoint can be defined at a location spaced a distance from the border. In some embodiments, a waypoint can be defined on the border along the threshold. In some embodiments, two waypoints can be defined in association with a threshold spaced at locations on opposite sides of the border along the threshold. In some embodiments, two waypoints can define a start and an end of a passageway across a threshold, for example, to provide efficient one-way travel along the passageway.
Waypoints can be defined by reference to a point of origin 110, as described above with respect to
In order to manage such navigation, as shown in
In some embodiments, the robot may configured to pass over a waypoint, and traverse the threshold without stopping. In some embodiments, upon arriving at a waypoint, a robot may be configured to pause before traversing the threshold. In some embodiments, after pausing at the waypoint, the robot may determine if the threshold is clear of traffic, for example, using a camera, a laser detector, or a radar detector, or a combination thereof, as described above, before crossing the threshold. In some embodiments, upon arriving at a waypoint, a robot can receive further instructions or commands from the robot monitoring server regarding whether or not to traverse the threshold. Such instructions or commands can either be pushed automatically from the server or be in response to a request by the robot. By requiring the robot to pass over or pause at the waypoint, the navigation of the robot across the threshold is controlled, directing passage of the robot across zone borders (physical or virtual).
In some embodiments, the robot may be configured to join a queue of robots waiting to traverse the threshold. For example, another robot may already be paused at the pose location defining the waypoint. And, one or more other robots may be waiting in queue locations to also cross the threshold at the appropriate time. The newly arriving robot can join a queue slot or location, offset from the pose location of the waypoint and/or offset from the pose locations of other robots waiting in the queue to traverse the threshold. The queueing of robots may be managed, for example, by the navigation server or a warehouse management server 15.
For example, when one or more robots attempt to navigate to a space occupied by another robot, alternative destinations for the robots are created to place them in a queue and avoid a “race condition” from occurring. When another robot tries to navigate to an occupied, the robot is redirected to a temporary holding location or queue slot offset from the occupied pose. The locations of the queue slots may be non-uniform and variable given the dynamic environment of the warehouse. The queue slots maybe offset according to a queuing algorithm that observes the underlying global map and the existing obstacles and constraints of the local map. The queuing algorithm may also consider the practical limits of queuing in the space proximate the target location/pose to avoid blocking traffic, interfering with other locations, and creating new obstacles.
In addition, the proper queue slotting of robots into the queue can be managed, such that a robot with a first priority to occupy the pose may be queued in the first queue slot, while the other robots are queued in the other queue slots based on their respective priorities. Priorities may be determined by the order of the robots' entry into a zone proximate the pose. When a robot moves from the pose (target location), a next robot moves from the queue slot to the pose, and any other robots can advance in queue slot positions, respectively. Thus, the manner in which the robots are navigated to the queue slots and ultimately the target location is accomplished by temporarily redirecting them from the pose of the target location to the pose(s) of the queue slot(s). In other words, when it is determined that a robot must be placed in a queue slot, its target pose is temporarily adjusted to a pose corresponding to the location of the queue slot to which it is assigned. As it moves up in position in the queue, the pose is again adjusted temporarily to the pose of the queue slot with the next highest priority until it is able to reach its original target location at which time the pose is reset to the original target pose. Queueing of robots is described further in U.S. Pat. No. 10,513,033, issued on Dec. 24, 2019, entitled “ROBOT QUEUING IN ORDER FULFILLMENT OPERATIONS,” the disclosure of which is incorporated by reference herein.
In some embodiments, the route may require the robot to navigate to a zone having an elevation different from an elevation of an adjacent zone. In some embodiments, the threshold may cross a sloped surface or ramp between the zones. In some embodiments, depending on the degree of slope, two waypoints can define a start and an end of a passageway along the slope across the threshold. In some embodiments, an elevator can be provided to transport a robot from one zone to another. A threshold can be defined at the elevator door, such that a robot can arrive at a waypoint associated with the elevator and can request and/or issue an instruction(s) to call the elevator, open the elevator door so that the robot can enter the elevator, and direct the elevator to the next zone.
By way of further description, in the absence of a threshold defined in a virtual barrier, a robot might determine that a route that passes close to the end of a physical barrier is the shortest route to a destination. For example, the robot 18′, indicated by a dashed line in
The server can be any server or computing device capable of tracking robot and/or human operator activity within the warehouse, including, for example, the warehouse management system 15, the order-server 14, a standalone server, a network of servers, a cloud, a processor and memory of the robot tablet 48, the processor and memory of the base 20 of the robot 18, a distributed system comprising the memories and processors of at least two of the robot tablets 48 and/or bases 20. In some embodiments, the waypoint information can be pushed automatically from the robot monitoring server 902 to the robot 18. In other embodiments, the waypoint information can be sent responsive to a request from the robot 18.
Thus, the navigation management system and method can advantageously direct a robot through a navigational space that has been divided into zones more efficiently, with lower collision risk, and can prevent inefficient delays in robot task completion.
Virtualization can be employed in the computing device 1210 so that infrastructure and resources in the computing device can be shared dynamically. A virtual machine 1224 can be provided to handle a process running on multiple processors so that the process appears to be using only one computing resource rather than multiple computing resources. Multiple virtual machines can also be used with one processor.
Memory 1216 can include a computational device memory or random access memory, such as but not limited to DRAM, SRAM, EDO RAM, and the like. Memory 1216 can include other types of memory as well, or combinations thereof.
A user can interact with the computing device 1210 through a visual display device 1201, 111A-D, such as a computer monitor, which can display one or more user interfaces 1202 that can be provided in accordance with exemplary embodiments. The computing device 1210 can include other I/O devices for receiving input from a user, for example, a keyboard or any suitable multi-point touch interface 1218, a pointing device 1220 (e.g., a mouse). The keyboard 1218 and the pointing device 1220 can be coupled to the visual display device 1201. The computing device 1210 can include other suitable conventional I/O peripherals.
The computing device 1210 can also include one or more storage devices 1234, such as but not limited to a hard-drive, CD-ROM, or other computer readable media, for storing data and computer-readable instructions and/or software that perform operations disclosed herein. Exemplary storage device 1234 can also store one or more databases for storing any suitable information required to implement exemplary embodiments. The databases can be updated manually or automatically at any suitable time to add, delete, and/or update one or more items in the databases.
The computing device 1210 can include a network interface 1222 configured to interface via one or more network devices 1232 with one or more networks, for example, Local Area Network (LAN), Wide Area Network (WAN) or the Internet through a variety of connections including, but not limited to, standard telephone lines, LAN or WAN links (for example, 802.11, T1, T3, 56 kb, X.25), broadband connections (for example, ISDN, Frame Relay, ATM), wireless connections, controller area network (CAN), or some combination of any or all of the above. The network interface 1222 can include a built-in network adapter, network interface card, PCMCIA network card, card bus network adapter, wireless network adapter, USB network adapter, modem or any other device suitable for interfacing the computing device 1210 to any type of network capable of communication and performing the operations described herein. Moreover, the computing device 1210 can be any computational device, such as a workstation, desktop computer, server, laptop, handheld computer, tablet computer, or other form of computing or telecommunications device that is capable of communication and that has sufficient processor power and memory capacity to perform the operations described herein.
The computing device 1210 can run any operating system 1226, such as any of the versions of the Microsoft® Windows® operating systems (Microsoft, Redmond, Wash.), the different releases of the Unix and Linux operating systems, any version of the MAC OS® (Apple, Inc., Cupertino, Calif.) operating system for Macintosh computers, any embedded operating system, any real-time operating system, any open source operating system, any proprietary operating system, or any other operating system capable of running on the computing device and performing the operations described herein. In exemplary embodiments, the operating system 1226 can be run in native mode or emulated mode. In an exemplary embodiment, the operating system 1226 can be run on one or more cloud machine instances.
While the foregoing description of the invention enables one of ordinary skill to make and use what is considered presently to be the best mode thereof, those of ordinary skill will understand and appreciate the existence of variations, combinations, and equivalents of the specific embodiments and examples herein. The above-described embodiments of the present invention are intended to be examples only. Alterations, modifications and variations may be effected to the particular embodiments by those of skill in the art without departing from the scope of the invention, which is defined solely by the claims appended hereto. The invention is therefore not limited by the above described embodiments and examples.
Having described the invention, and a preferred embodiment thereof, what is claimed as new and secured by letters patent is: