Automatic publishing system

Abstract

The disclosed technology includes a robotic sales assistant that receives items from sellers, automatically generates a posting describing the item for sale, stores the item until it is sold, and delivers the item or sends it out for delivery. The item is placed in a compartment that uses one or more sensors to identify the item, retrieves supplemental information about the item, and takes a photo of the item to include in the posting. The description of the item provided by the seller can be verified based on the retrieved supplemental information, thereby preventing the sale of mislabeled items.

Description

Technical Field

[0001] The present disclosure relates to a computer operated vehicle, a computer system, and a computer readable storage medium. Background Art

[0002] Hundreds of billions of dollars are spent on online purchases every year. While the popularity of the Internet and the reduction in shipping costs have increased online sales, many aspects of online sales remain cumbersome and time-consuming. For example, creating a posting listing an item for sale requires describing the item, taking photos of the item, identifying the manufacturer, model, and year of production, assessing the item's condition, and estimating shipping costs. These tasks are particularly onerous for individual sellers and sellers of used items because the time and expense cannot be recouped through large sales. Other challenges for online sales include storing items until they are sold, determining how to package the items, and transporting the packaged items to a delivery service. As a result, many items that would otherwise be sold are kept in storage or simply thrown away. Among those items that do sell, low-quality postings often drive down prices, making the situation worse for sellers and online sales platforms.

[0003] Another problem faced by online sellers and the platforms they operate is inaccurate listings. Sellers may intentionally or unintentionally mislabel items, misstate the condition of items, misstate the functionality of items, etc. Inaccurate listings, whether accidental or intentional, can damage the reputation of sellers and online selling platforms.

[0004] It is with respect to these and other technical considerations that the present disclosure made herein is proposed. Summary of the invention

[0005] A robotic automatic publishing system is provided and described herein. In one embodiment, a robotic sales assistant receives an item from a seller, automatically generates a publication describing the item, stores the item until the item is sold, and sends the item out for delivery. The robotic sales assistant may be an autonomous vehicle that drives to the item, extracts the item, and places the item in a publishing compartment. The publishing compartment may include multiple sensors and electronic devices for identifying the item, verifying whether the item meets the seller's requirements, and generating a publication describing the item. Once the item is sold, the robotic sales assistant may hand the item over to a packaging delivery company or deliver the item directly to the buyer.

[0006] The robotic sales assistant may use a camera to capture images of the item for inclusion in the posting. The robotic item manipulation arm and / or turntable may lift, rotate, or otherwise manipulate the item to expose different perspectives to the camera. A three-dimensional rendering of the item may be created by capturing a series of images as the item rotates on the turntable or as one or more cameras rotate around the item. By including many images from various perspectives, the quality of the posting may be improved.

[0007] Images can also be used to identify items. The robotic sales assistant can identify barcodes, QR codes, brands, models, serial numbers, or other identifying information from images of items. In other embodiments, the robotic sales assistant can use a machine learning-based image recognition system to identify items.

[0008] The identity of the item can be used to generate a description to include in the posting. The identification information can be included directly in the description. The identification information can also be used to retrieve a description, user manual, or other more detailed information about the item to include in the posting.

[0009] The identity of the item can also be used to confirm the description of the item provided by the seller. If the identity of the item does not match the description provided by the seller, the robotic sales assistant can alert the seller of the discrepancy. The robotic sales assistant can also ask the seller whether to proceed with the sale or whether the item should be returned to the seller. If the robotic sales assistant determines that the seller has intentionally misdescribed the item, the robotic sales assistant can alert the online sales platform of potential fraudulent activity.

[0010] In some embodiments, the robotic sales assistant can determine the weight and one or more dimensions of the item. The weight can be determined based on a scale, while the dimensions can be determined based on a 3-D model or laser-based measurements. The weight and dimensions of the item can be included in the listing as part of the item description, used to estimate the size and quantity of packaging materials suitable for the item, used to estimate shipping costs, and / or used to verify the description of the item provided by the seller.

[0011] In some embodiments, the robotic sales assistant includes a robotic arm that creates custom packaging to fit the measured dimensions. The custom packaging can be made of one or more materials such as cardboard, plastic, bubble wrap, or paper, and the custom packaging can take the form of a box, bubble wrap envelope, tube, flat envelope, etc. For example, the robotic sales assistant can cut and fold a box, construct a cardboard tube, cut and fold a bubble wrap envelope, or otherwise construct custom packaging to fit the measured dimensions of the item.

[0012] The robotic arm is not limited to shapes such as cylinders or cuboids, but can construct custom shapes consistent with the shape of the item based on a 3-D model. Conformal packaging can reduce the material cost of packaging. Conformal packaging can also reduce the volume of the package, which can reduce storage and transportation costs.

[0013] Before packaging the item with the customized packaging, the robotic sales assistant may apply protective padding to the item. For example, the robotic sales assistant may dispense and / or apply special packaging materials or packaging, such as bubble wrap, paper, or foam, to items identified as fragile. The amount of special packaging material applied may be based on the measured dimensions of the item, a 3-D model, the determined fragility of the item, etc. The item may be identified as fragile based on a determination of the materials used to make the item, the size of the item, historical damage rates of similar items, etc. Padding may increase the size of the item, and therefore the robotic sales assistant may include increasing the size of the item when constructing the customized packaging.

[0014] Additional sensors can be used to determine the condition of the item. Infrared sensors, ultraviolet sensors, light intensity sensors, etc. can be used to determine if the item was damaged before receipt, or the degree to which the item is worn. For example, hyperspectral imaging can use light beyond the normal human visual range to infer the age of the item. Microphones can be used to determine if the item makes an unexpected rattling sound when moved. Sensors that measure light intensity can be used in conjunction with cameras to determine if the item is worn or dirty.

[0015] The robotic sales assistant may also include a computing device interface to identify and assess the condition of an electronic item. For example, the robotic sales assistant may insert a universal serial bus (USB) cable into an item to verify the item's identity. The robotic sales assistant may also use Bluetooth, Wi-Fi, or other wireless connections to connect to the item and determine the item's identity. In addition, the robotic sales assistant may utilize the computing device interface to determine attributes of the item that are not apparent from an image, serial number, or other external identifying information. For example, the robotic sales assistant may use a USB connection to determine the capacity of a storage device within an electronic item.

[0016] By performing many of the tasks of selling items, the robotic sales assistant reduces the overhead incurred by the seller. This increases the number of items worth selling for the seller. By generating more comprehensive listings that include pictures, identification information, and comprehensive descriptions, the robotic sales assistant can improve sales volume and gross margin. By retrieving and storing items to be sold, the robotic sales assistant reduces the seller's storage costs, thereby further increasing the number of items worth selling. And by ensuring that listings are accurate, the reputation of the seller and the online sales platform is improved.

[0017] It should be understood that the subject matter described above and described in further detail below can be implemented as a computer-controlled apparatus, a computer-implemented method, a computing device, or an article such as a computer-readable storage medium. These and various other features will be apparent by reading the following detailed description and viewing the associated drawings.

[0018] This summary is provided to introduce a series of concepts in a simplified form, which are further described in the detailed description below. This summary is neither intended to identify the key features or essential features of the claimed subject matter, nor is this summary intended to be used to limit the scope of the claimed subject matter. In addition, the claimed subject matter is not limited to implementations that address any or all of the disadvantages mentioned in any part of this disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The detailed description is described with reference to the accompanying drawings. In the drawings, the leftmost digit(s) of a reference number identifies the drawing in which the reference number first appears. The same reference numbers in different drawings indicate similar or identical items.

[0020] Figure 1A is a system diagram of an exemplary robotic sales assistant;

[0021] Figure 1B is an overview of the route of an exemplary robotic sales assistant;

[0022] Figure 2A is a block diagram illustrating aspects of a publishing compartment according to one embodiment disclosed herein;

[0023] Figure 2B is a block diagram illustrating aspects of a release bay when capturing images of an item from multiple angles;

[0024] Figure 2C is a block diagram illustrating aspects of a release compartment when inserting a communications cable into an article;

[0025] Figure 3A is a diagram illustrating aspects of a release generated by a robotic sales assistant according to one embodiment disclosed herein;

[0026] Figure 3B is a diagram illustrating aspects of another release generated by a robotic sales assistant according to one embodiment disclosed herein;

[0027] Figure 4 is a flow chart showing aspects of an illustrative routine according to one embodiment disclosed herein;

[0028] Figure 5is a flow chart showing aspects of an illustrative routine according to one embodiment disclosed herein;

[0029] Figure 6 is a computer architecture diagram illustrating aspects of an example computer architecture for a computer capable of executing the software components described herein.

[0030] Figure 7 is a data architecture diagram showing an illustrative example of a computer environment. DETAILED DESCRIPTION

[0031] The following detailed description presents techniques for an autonomous vehicle that receives an item and automatically generates a posting describing the item. In various embodiments, one or more sensors in conjunction with a robotic arm or turntable are used to identify the item. Once identified, the robotic sales assistant can retrieve additional information about the item, generate a posting describing the item, store the item, and / or move the item to a warehouse until the item is sold. The robotic sales assistant can also package the item, deliver the item to a purchaser, and / or transport the item to a delivery service for delivery to the purchaser.

[0032] The disclosed techniques can enhance the functionality and efficiency of item identification and description. As just one example, by correctly identifying items and generating complete and accurate descriptions of those items, items can be sold faster, thereby reducing the amount of computing resources required to sell those items. At the same time, when a desired item has been completely and accurately described using the disclosed techniques, a purchaser can expend less computing resources to locate the desired item. In this way, the disclosed techniques improve the performance and efficiency of computing devices.

[0033] The disclosed technology can also improve the detection of mislabeled or counterfeit items. Correct identification of items also allows more efficient packaging. Technical benefits other than those specifically mentioned herein can also be achieved through implementation of the disclosed technology.

[0034] It should be understood that although the technology disclosed herein is primarily described in the context of online sales, the technology described herein can also be used to identify, describe, package and / or transport items in other contexts, which will be apparent to those skilled in the art.

[0035] With reference to the accompanying drawings, in which like reference numerals represent like elements throughout the several drawings, various aspects of various technologies for an automatic publishing system will be described. In the following detailed description, reference is made to the accompanying drawings which form a part hereof, and which are shown by way of illustration of specific configurations or examples.

[0036] exist Figure 1A, a robotic sales assistant 100 implementing an automated posting system is shown. In some embodiments, a seller 107 of an item 104 requests the robotic sales assistant 100 to perform some or all of the steps for selling the item 104, such as retrieving the item 104 from a pickup location 108 designated by the seller, generating a posting describing the item 104 and indicating that the item 104 is for sale, storing the item 104 until the item 104 is sold, packaging the item 104, and / or providing the item 104 to a packaging delivery service 110 for delivery to a purchaser. The seller 107 may request some or all of these actions from a sales device 113, which may be a smart phone, tablet, laptop, or other computing device. For example, the seller 107 may use the sales device 113 or an application running on the sales device 112 to take a photo of the item 104, write a description of the item 104, set a seller-designated pickup location 108, and / or request that the item 104 be picked up at the seller-designated pickup location 108.

[0037] In some embodiments, the robotic sales assistant 100 may be an autonomous vehicle capable of driving to a pickup location 108 designated by the seller (also referred to as a “pickup location 108”). In other embodiments, the robotic sales assistant 100 may be a portable unit that is towed to the pickup location 108 designated by the seller. In yet other embodiments, the robotic sales assistant 100 may be a drone 109 or other unmanned aerial vehicle capable of flying to the pickup location 108 designated by the seller. In some embodiments, the seller 107 uses the sales device 113 to set up the designated pickup location 108 and request a pickup. However, the robotic sales assistant 100 need not move at all, but may be permanently located in a store, mall, or other convenient location, in which case the seller 107 may bring the item 104, at least in part, to the robotic sales assistant 100 for processing.

[0038] Although FIG. 1 depicts the robotic sales assistant 100 as a single vehicle, different functional aspects of the robotic sales assistant 100 may be performed by different vehicles. For example, the robotic sales assistant 100 may be a fixed unit located, for example, in a shopping mall. The retrieval vehicle 101 ( Figure 1AThe retrieval vehicle 101 may be a truck, car, or other vehicle that works with the robotic sales assistant 100. The retrieval vehicle 101 may be dispatched to a pickup location 108 designated by the seller to retrieve an item 104 for processing by the robotic sales assistant 100. The retrieval vehicle 101 may then meet up with the robotic sales assistant 100 and use the grappling hook 106 to place the retrieved item 104 in the release compartment 102. In another embodiment, one or more drones 109 may work in conjunction with the robotic sales assistant 100. When the robotic sales assistant 100 is stationary, the drone 109 may retrieve the item 104 from the pickup location 108 designated by the seller. For example, the drone 109 may retrieve the item 104 from the pickup location 108 designated by the seller in a shopping mall parking lot. In another embodiment, the robotic sales assistant 100 or the retrieval vehicle 101 may be equipped with one or more drones 109. Such a mobile robotic sales assistant 100 may drive by nearby, thereby dispatching a drone 109 to retrieve an item 104 from a pickup location 108 designated by the seller.

[0039] The robotic sales assistant 100 includes one or more release compartments 102 where items 104 can be placed for processing. In some embodiments, the items 104 are placed in the release compartment 102 by the seller 107, while in other embodiments, the grappling hook 106 or drone 109 retrieves the items 104 and places the items 104 in the release compartment 102. The seller 107 can gain access to the release compartment 102 through an automatic door 114. The automatic door 114 can be secured by a password, security token, biometric scanner, or other security credentials to ensure that only authorized persons can access the release compartment 102. Figure 2A The publishing compartment 102 is described in more detail.

[0040] Seller 107 can also use these security credentials to log in to online sales platform.Once logged in, seller 107 just can view the publication of item 104, edit publication, update publication or delete publication.

[0041] Once the robotic sales assistant 100 has received the item 104, the robotic sales assistant 100 may generate a posting advertisement for the item 104 for sale. In some embodiments, the robotic sales assistant 100 stores the item 104 until the item 104 is sold. In other embodiments, the robotic sales assistant 100 transfers the item 104 to the warehouse 112 until the item 104 is sold. At any time while the item 104 is in the custody of the robotic sales assistant 100 or the warehouse 112, the robotic sales assistant 100 may select packaging materials that may be used to package the item 104. The selection may be made based on attributes of the item 104 measured by the posting compartment 102, such as size, weight, condition, fragility, etc. The packaging materials may also be selected based on supplemental information 222 about the item 104 (e.g., Figure 2A The robotic sales assistant 100 can identify fragile items based in part on the materials used to make the items. For example, items made of glass, electronic components, or parchment can be considered fragile, while items made of plastic or binder paper can be considered less fragile. The material from which the item is made can be determined by one or more of sensors 204 to 214, or based on analysis of supplemental information 222. Special packaging such as bubble wrap, rigid containers, etc. can be applied to fragile items to reduce the likelihood that the fragile items will be damaged during storage and shipping.

[0042] In some embodiments, the robotic sales assistant 100 includes a computing device 130 that can execute instructions included in a memory to implement various aspects of the embodiments. The computing device 130 can implement the following in combination with Figure 2A The object recognition engine 218 described below is combined with Figure 6 and Figure 7 The computing device 130 is described in more detail. The robotic sales assistant 100 can utilize the network(s) 120 to communicate with the server device 140. The server device 140 can host the postings generated by the robotic sales assistant 100. The server device 140 can also make the postings available to potential buyers 111. The robotic sales assistant 100 can also utilize the network(s) 120 to retrieve supplemental information 222 about the item 104, such as a product description, product brochure, etc.

[0043] Figure 1BAn overview of the route of an exemplary robotic sales assistant 100 is shown. In this example, the robotic sales assistant 100 has left the warehouse 112 to retrieve an item 104 from a seller pickup location 108. In some embodiments, the robotic sales assistant 100 works in conjunction with a retrieval vehicle 101, which can also retrieve the item 104 and / or launch a drone 109 to retrieve the item 104.

[0044] Figure 1B Three streets and three seller pickup locations are depicted, with one seller pickup location on each street. Seller pickup location 108A is on Main street 118A, seller pickup location 108B is on Ashland Ave 118B, and seller pickup location 108C is on Thomas Ave 118C. Drone 109 along with a truck navigating along street 118 to seller pickup location 108 is one embodiment of the disclosed technology. However, any type of vehicle such as a boat, train, bicycle, or hovercraft traveling along any type of avenue such as a railroad line, canal, or sky corridor is similarly contemplated. In addition, although Figure 1B A truck is shown working in conjunction with a drone, but any combination of vehicles is similarly contemplated. For example, a cargo ship is similarly contemplated along with a ute, a train is similarly contemplated along with a truck, etc., or a combination thereof.

[0045] Figure 1B The robotic sales assistant 100 is shown on a route 150 for picking up one or more items 104 at seller pickup locations 108A, 108B, and 108C. The robotic sales assistant 100 can plan the route 150 based on a number of factors, such as: travel time to each of the seller pickup locations 108 and travel time between each of the seller pickup locations 108. The speed and capacity of the vehicles used to pick up items and process the items are also factors, such as: the number of drones 109, drone capacity, the number of retrieval vehicles 101, and retrieval vehicle capacity.

[0046] The characteristics of the items being retrieved are also factors in vehicle selection and route planning, such as: the number of items 104 at each pickup location 108, the estimated weight and size of the total items 104, individually and for each pickup location 108, the type of item - for example, whether the item is flammable, fragile, of high value, etc. In some embodiments, the seller 107 manually enters a description of the item 104, including weight, size, flammability, fragility, value, etc. In other embodiments, these characteristics can be derived from the posting, including pictures, descriptions, descriptions of other postings for similar or identical items 104, product brochures, and other information linked from the posting. The type of vehicle can be selected for a particular route 150 based on the characteristics of the items 104 to be picked up. The type of vehicle can be selected to meet the individual requirements of the items 104 to be picked up, for example, a vehicle with a powerful robotic arm can be selected for a route 150 including heavy items 104. The type of vehicle can also be selected to meet the collective requirements of the items 104 picked up on the route, such as total volume, weight, refrigeration requirements, etc.

[0047] Characteristics of the robotic sales assistant 100 itself are also factors in route planning, including the number and processing speed of the release bays 102, the available item storage capacity 105 for the robotic sales assistant 100 to store processed items 104, etc. The route 150 can define the path taken by each vehicle, the drone launch point 120, the drone collection point 122, and the schedule for when the items 104 will be processed by the release bays 102.

[0048] For example, travel time can be calculated based on the distance between the robot sales assistant 100, the retrieval vehicle 101, the drone 109 and the item 104. For all vehicles, the distance along the navigable road 118 is considered. However, drones may not always be limited by roads, and thus straight-line (i.e., Euclidean) distances may also be considered. Travel time may also be affected by road conditions, weather, traffic, and other obstacles. Estimated collection time - i.e., the time required for the vehicle to secure the item 104 in order to travel - may also be a factor in the travel time when retrieving items along the route.

[0049] The route selection may also be affected by the number, weight, size, and type of items 104 at each pickup location 108. The number, weight, size, and type of items to be retrieved may be analyzed based on the drone capacity. For each drone 109, the drone capacity may determine the weight, size, number, and type (e.g., flammable, fragile, etc.) of the items that the drone can retrieve in one or more passes. In some embodiments, the drone capacity is compared to the item weight, size, and type to determine whether the drone can retrieve the item. The weight, size, and type of each item may also be used to determine whether multiple items 104 can be retrieved simultaneously from a single pickup location in a single trip, whether multiple items 104 can be retrieved from multiple pickup locations 108 before unloading them, etc. If the collective weight of the items is too large or if the space required by the items collectively exceeds the carrying capacity of the drone, the drone may not be able to retrieve multiple items in a single trip. Based on these limitations, even if the drone 109 is best positioned to travel to the pickup location 108, the drone 109 may not be able to retrieve the item at that location, and therefore the robotic sales assistant 100 may be more efficient in retrieving the item.

[0050] However, the drone 109 is not limited to a single trip to a specific pickup location 108 - the robotic sales assistant 100 can plan a route in which the drone 109 repeatedly moves items from one or more pickup locations 108 to a staging area. In some embodiments, the staging area is an area that the robotic sales assistant 100 or retrieval vehicle 101 will pass through / return to as part of the route 150. The items can accumulate at the staging area until the robotic sales assistant 100 returns to process the items. In this way, a drone 109 that is not able to retrieve multiple items 104 from a pickup location 108 in the same trip can retrieve multiple items 104 from the pickup location 108 in multiple trips and unload the items 104 to the staging area.

[0051] The route 150 may be optimized in a variety of ways. The route 150 may be optimized to retrieve the item as quickly as possible—that is, the route 150 may be optimized so that the item 104 is retrieved and placed into the robotic sales assistant 100 in the least amount of time. Additionally or alternatively, the route 150 may be optimized to minimize energy costs. The route 150 may also be optimized to minimize drone flight time around noise-sensitive areas.

[0052] In some embodiments, the route 150 is optimized to maximize the throughput of item processing. The robot sales assistant 100 may have a limited number of release bays 102 for processing items, and therefore it may be advantageous to plan the route 150 so that a steady stream of items is provided to the robot sales assistant 100 to maximize the use of the release bays 102. Maximizing the throughput of item processing is different from retrieving all items as quickly as possible, because the robot sales assistant 100, the retrieval vehicle 101, and the drone 109 can be routed to provide items to the release bays 102 for processing early in the route and throughout the route. In contrast, if most or all of the items become available for processing at the end of the route, the release bays 102 will become backlogged, and the robot sales assistant 100 will be idle while the backlog is processed. By maximizing the throughput of the release bays 102, the route 150 can allow the robot sales assistant 100 to eliminate backlogs in processing multiple groups of items. In some embodiments, route 150 is optimized so that the robotic sales assistant is processing the last items 104 when it returns to warehouse 112, thereby filling item storage device 105, at which time the processed items 104 can be unloaded and the robotic sales assistant 100 can embark on another route 150 to retrieve a new set of items 104.

[0053] In some implementations, the route 150 is planned based on the number and capacity of the retrieval vehicles 101 that work with the robotic sales assistant 100. The route 150 may also be planned based on the number and capacity of the drones 109 that are available for the robotic sales assistants 100 and the retrieval vehicles 101. The speed at which the drones can be launched and collected may also be a factor in planning the route 150.

[0054] like Figure 1B As depicted, the robotic sales assistant 100 has driven down Ashland Avenue and launched drones 109A and 109B to retrieve items from seller pickup locations 108A and 108B. Drone 109A was launched from drone launch point 120A, while drone 109B was launched from drone launch point 120B. In this example, the robotic sales assistant 100 works in conjunction with a retrieval vehicle 101, which launches drone 109C from drone launch point 120C. Each drone 109 flies to a corresponding seller pickup location. As the robotic sales assistant 100 travels along road 118, the drones 109 can fly over or around obstacles, thereby increasing the effective range of the robotic sales assistant 100 and allowing for parallel retrieval of items 104.

[0055] In some embodiments, route 150 may identify drone collection points 122 at which the robotic sales assistant 100 collects drones 109 that have retrieved items 104 from pickup locations 108. For example, drone 109A may meet the robotic sales assistant 100 at drone collection point 122A, having retrieved item 104A from seller pickup location 108A. Similarly, drone 109B may meet the robotic sales assistant 100 at drone collection point 122B, while drone 109C may meet the retrieval vehicle 101 at drone collection point 122C. Items collected by the retrieval vehicle 101 may be transferred to the robotic sales assistant 100 at a truck handover point 124.

[0056] The robotic sales assistant 100 can place items in the staging bay 103 while making the release bay 102 available for processing the staging items. Once a release is generated for an item by the release bay 102, the item can be transferred to the item storage device 105, where the item can wait to be unloaded to the warehouse 112, delivered to the buyer 111, or packaged for transfer to the package delivery service 110.

[0057] Figure 2A A block diagram 200 is shown showing aspects of a release booth 102 according to one embodiment disclosed herein. An item 104A, in this example a smart phone, has been placed on top of a turntable 202. The item 104A may be placed on the turntable 202 by a seller 107, a grapple 106 of a robotic sales assistant 100, a grapple 106 of a retrieval vehicle 101, a drone 109, or the like. In some embodiments, an item manipulation arm 216 places the item 104 on the turntable 202, or the item manipulation arm 216 may center the item 104 on the turntable 202. In another embodiment, the item 104 is placed on a non-rotating table, a scale 204, or other surface that cannot be used as a turntable.

[0058] Once placed on the turntable 202, the items 104 may be analyzed by one or more sensors such as a scale 204, a camera 206, an ultraviolet camera 208, an infrared camera 210, a barcode reader 211, a microphone 212, a communication cable 213 (e.g., a USB cable), a laser distance measuring device 214, and / or an odor sensor 215. The items 104 may be physically manipulated by the turntable 202 or the item manipulation arm 216 before, during, or after obtaining information about the items 104 from one or more of the above sensors. In this manner, the item manipulation arm allows the sensors to perceive the items 104 from different perspectives.

[0059] Scale 204 may be used to determine the weight of item 104. As discussed in more detail below, the weight of an item may be used to determine shipping costs, select packaging materials, and detect counterfeit items.

[0060] Camera 206 (also referred to herein as sensor 206) may be any device that captures still images and / or video. One or more still images and / or video 308 (e.g., Figure 3A 204) to the posting to help potential buyers evaluate the offered item 104 and to provide assurance to potential buyers of the item's condition. The camera 206 may also capture intensity values ​​that may be used to identify wear and tear on the item 104. In some embodiments, the camera 206 captures images of the item 104 as the turntable 202 rotates, thereby ensuring that the item 104 is photographed from multiple angles. Additionally or alternatively, the item handling arm 216 may pick up the item 104 and present different perspectives to the camera 206 to generate images from different angles. For example, the item handling arm 216 allows a portion of the item 104 placed on the turntable 202 to be photographed.

[0061] Ultraviolet (UV) camera 208 generates images based on invisible light from the ultraviolet spectrum. UV light can be used to determine the condition of an item and / or infer the age of an item. For example, worn portions of an item may have different patterns in an image captured by UV camera 208. The degree of wear on the item may provide a representation of the age and condition of item 104. The age and condition of the item, in turn, may be a factor in estimating the remaining useful life of item 104.

[0062] Additionally or alternatively, UV camera 208 may be used in conjunction with UV light to capture UV-induced fluorescence. UV-induced fluorescence may identify the presence of physiological fluids such as saliva and urine, as well as mold and other residues left on item 104. Detection of one or more of these residues may be used to update the estimated condition of item 104. Detection of one or more of these residues may also be used in publishing 305 ( Figure 3A ) of one or more captured images 308 or descriptions 314 ( Figure 3A ) is highlighted.

[0063] The infrared (IR) camera 210 generates an image based on invisible light from the infrared spectrum. IR light can be used to estimate the temperature of an item, i.e., thermal imaging. In one embodiment, the item 104 can have a specified operating temperature range. The robotic sales assistant 100 can open the item 104 and measure the temperature of the item 104 using the infrared camera 210 while using the item 104. The measured temperature can be compared to the specified temperature range, or to the temperature of an item comparable to the item 104. Deviations from the specified temperature range can be noted in the description 314 of the release 305 and can be used as a factor in determining the condition of the item 104. In one embodiment, the robotic sales assistant 100 can use the communication cable 213 to manipulate the item 104 while testing for overheating. In one embodiment, the robotic sales assistant 100 can use the item manipulation arm 216 to open the item 104A.

[0064] IR camera 210 may also be used to detect the presence of water on / in an item, and thus detect potential water damage in item 104. For example, IR camera 210 may sense lower temperatures where water or other liquids evaporate within item 104. Water damage may be another factor included in determining the condition of item 104.

[0065] The camera 206, UV camera 208, IR camera 210, or a combination thereof can be used in conjunction with an image processing algorithm to detect stains on the item 104. One image processing algorithm identifies common stains, such as grass, blood, oil, crayon, bleach, etc. Another image processing algorithm identifies decorative patterns on the item 104, such as polka dots, herringbone, or stripes, and then identifies portions of the item 104 that deviate from the pattern as stains. Another image processing algorithm identifies fading, corrosion (e.g., rust), and other forms of wear on the item 104. The image processing algorithm can be hand-coded based on machine learning or a combination thereof. The presence of a stain - including a picture highlighting the stain - can be included in the posting. The presence of a stain can also be used when estimating the condition of the item 104 and / or the suggested price of the item 104.

[0066] The article handling arm 216 itself can be used to test the condition of the article 104. For example, the article handling arm 216 can apply a force to the article 104 to determine the flexibility of the article 104. The article handling arm 216 can apply the force against the scale 204 to measure the amount of force applied. In another embodiment, two or more article handling arms can be used to push, pull, squeeze, twist, or otherwise apply force to the article 104 to determine physical characteristics including flexibility, rigidity, firmness, etc.

[0067] The camera 206 can measure the amount of pushing, pulling, squeezing, twisting, and other physical deformations caused by one or more of the item manipulation arms 116. For example, the camera 206 can capture an image of the item 104 during a flexibility test, and the image processing algorithm can measure the amount of flexibility induced by the item manipulation arm 216. Flexibility, rigidity, firmness, etc. can imply item condition, and therefore price, e.g., if some vegetables are flexible, then the vegetables can be considered to be in poor condition, while if a metal tube is rigid, then the metal tube can be considered to be in good condition. In some embodiments, the condition of the item 104 can be estimated by comparing the measured flexibility value with an expected flexibility value derived from historical measurements of similar items, published specifications for item flexibility, etc.

[0068] Odor sensor 215 may be used to determine the condition of item 104. Odor sensor 215 may capture particulate matter emitted by item 104 and perform chemical or spectral analysis on it to identify an odor. Odor sensor 215 may identify well-known odors such as perfume, urine, animal odors, smoke (e.g., cigarette smoke), gasoline, burnt or burning odors, mold, mildew, etc. In addition to taking into account the condition of item 104, the odor may also be added to the posting as part of the description.

[0069] The barcode reader 211 may be used to scan a barcode, QR code, or other encoded number displayed on the item 104. In one embodiment, the item recognition engine 218 causes the barcode reader 211 to scan the barcode 217 on the item 104 to determine the item identifier 220. The robotic sales assistant 100 may then use the item identifier 220 to query the server device 140 for supplemental information related to the item 104. The query for supplemental information may utilize the wireless network 120 to look up the supplemental information from the manufacturer's website or from any other public data source.

[0070] The microphone 212 can be used to record sounds emitted from the item 104. The microphone 212 can be used to determine the volume level of the item 104 when it is operating. For example, the robotic sales assistant 100 can robotically connect the communication cable 213 to the item 104, or otherwise open and operate the item 104. Once the item 104 is opened, the microphone 212 can determine whether the item 104 is operating within a specified decibel range - for example, whether it is operating within a decibel range specified by the item product manual, manufacturer, etc. The volume level detected using the microphone 212 can also be compared with the average volume level generated by similar items - for example, items with the same item identifier 220 previously measured by the robotic sales assistant. Whether the item 104 operates within the specified decibel range can be a factor in determining the condition of the item 104, for example, a lower volume can correspond to a better rating. In addition to the manufacturer-specified volume range, the description 314 of the item 104 can include the measured runtime volume.

[0071] The microphone 212 may also record audio as the item 104 is turned on the turntable 202 or held, shaken, tilted, rotated, or otherwise moved by the item manipulation arm 216. Based on the supplemental information 222 of the item 104, such as the contents of a product manual, product information retrieved from a manufacturer, etc., the robotic sales assistant 100 may determine whether any sounds are expected when the item 104 is moved. In other embodiments, the robotic sales assistant 100 may determine what sounds, if any, are expected by comparing to sounds emitted by similar items previously handled by the robotic sales assistant 100. For example, if the robotic sales assistant 100 has received thousands of toys with the same item identifier 220 for sale, and if the robotic sales assistant 100 has measured the sounds emitted from the toys when they are tilted, rotated, or otherwise manipulated by the item manipulation arm 216, the robotic sales assistant 100 may determine whether a new instance of the particular toy being evaluated produces the expected sounds when manipulated in the same manner. If the microphone 212 detects an unexpected sound, the condition of the item 104 in the description 314 of the item 104 may be updated accordingly, and the unexpected sound may be added to the description of the item. For example, the robotic sales assistant 100 may assign a condition of "fair" or "poor" to the item that produced the unexpected sound.

[0072] The communication cable 213 may be used to communicate with the item 104. The communication cable 213 may be, for example, a Universal Serial Bus (USB) cable, a Lightning cable, a serial cable, a 1394 The robot sales assistant 100 may be configured to communicate with the seller 107 via a communication cable 213, a lightning cable, etc. For example, the robot sales assistant 100 may open the item 104 via the communication cable 213. The robot sales assistant 100 may determine the item identifier 220 of the item 104 by querying system information, operating system information, manufacturer information, etc. Additionally or alternatively, the robot sales assistant 100 may cause the item 104 to perform a system check, the results of which may be included in the description of the release. In some embodiments, the computing device 130 uses login and password information provided by the seller 107 to access the item 104.

[0073] The communication cable 213 may also be used in conjunction with other sensors to perform tests on the item 104. The robotic sales assistant 100 may use the communication cable 213 to cause the item 104 to perform tests during which the microphone 212 measures the audio output. For example, the robotic sales assistant 100 may measure the sound level of the item's cooling fan while the item is in a loaded state. Similarly, the robotic sales assistant 100 may use the communication cable 213 to cause the item 104 to perform tests during which the infrared camera 210 may measure the temperature of the item 104. The results of these and other tests may be included in the description portion of the release.

[0074] Communications cable 213 may also be used to identify functionality included in item 104. For example, communications cable 213 may initiate a benchmark test to evaluate the speed, latency, and other performance metrics of item 104. Communications cable 213 may also identify features supported by item 104, such as software included in item 104, software versions, etc. Communications cable 213 may also be used to identify hardware components included in item 104, such as a specific display screen size, wireless network interface, etc. Item functionality may be included in a published description for estimating pricing, etc.

[0075] The communication cable 213 can also be used to detect counterfeit devices. For example, the computing device 130 can use the communication cable 213 to verify the description provided by the seller. The robot sales assistant 100 can insert the communication cable 213 into the item 104, thereby allowing the computing device 130 to scan the internal components of the item 104, such as memory, storage device, CPU, etc. The list of internal components can be compared with the list of internal components associated with the description provided by the seller. For example, if the description provided by the seller indicates that the smart phone has 128 gigabytes (GB) of storage space, but the internal scan performed using the communication cable 213 indicates that the item actually has 64 gigabytes, the seller and / or online sales platform can be notified. In another embodiment, the description provided by the seller can be excluded, or the description provided by the seller can be replaced in the release with a description generated based on the internal scan.

[0076] The communication cable 213 may also be used to detect counterfeit devices that package a cheaper, less capable, or otherwise less functional product within the housing / shell / enclosure of a more expensive, more capable, or otherwise more functional product. For example, a computer graphics card may appear to be a new, high-end product from a major graphics card manufacturer, when in fact the internal components are from an outdated, less capable graphics card. The item recognition engine 218 may compare the image-based identity with the list of internal components obtained from the communication cable 213 to determine whether the item is authentic or counterfeit.

[0077] In other embodiments, computing device 130 may use communications cable 213 to perform a factory reset of item 104. This prevents a seller from accidentally exposing personal information contained on item 104 to the public.

[0078] The laser distance measuring device 214 can be used to determine the size of the item 104. In one embodiment, the laser distance measuring device 214 is attached to a gimbal and moves up, down, left, right, forward, and backward relative to the item 104. In this way, distance measurements can be made to the item 104 in each of the three spatial dimensions. Additionally or alternatively, the laser distance measuring device 214 can rotate around the item 104 while keeping the focus on the center of the item 104A. In this embodiment, the laser distance measuring device 214 can identify the outline of the item 104, that is, by measuring the distance from the laser distance measuring device 214 to the item 104 while rotating the item 104. In either case, when the laser distance measuring device moves relative to the item 104, the laser distance measuring device 214 can determine the size of the item 104 by recording the distance between the item 104 and the laser distance measuring device 214.

[0079] In some implementations, the item identification engine 218 uses sensors contained in the publishing compartment 102 to identify the item 104—that is, to determine an item identifier 220. The item identifier 220 may include a unique number, such as a MAC address. The item identifier 220 may also include a product category combined with the unique number, such as the product category "books" combined with an International Standard Book Number (ISBN). In other domains, the item identifier may also include brand, model, and version information. One of ordinary skill in the art will appreciate that these are examples, and there are many other ways to uniquely identify an item.

[0080] Once determined, the item identifier 220 of the item 104 can be used to retrieve supplemental information 222 for the item 104. The supplemental information 222 can include the brand, model, manufacturer, model year, size, weight, color, version of installed software, manuals, links to manufacturer descriptions, etc. The supplemental information can also include the materials used to construct the item 104. By understanding the materials from which the item 104 is made, the robotic sales assistant 100 can better identify worn or damaged materials. For example, if the supplemental information 222 for the smart phone 104 indicates that the housing is made of aluminum, the UV camera 208 can be configured to identify wear and scratches on the aluminum. However, if the supplemental information 222 indicates that the item 104 is made of wood, cloth, stainless steel, leather, or any other material, the UV camera 208 and other wear detection sensors can be calibrated and utilized accordingly.

[0081] In one embodiment, the supplemental information may be used to select one or more angles, zoom levels, and distances of the camera 206 to obtain relevant and useful photos of the item 104. For example, the robotic sales assistant 100 may analyze photos included in a product brochure to determine the viewing angle, i.e., angle, zoom level, and distance, of the camera 206. The robotic sales assistant 100 may also consider the size, weight, and other dimensional aspects of the item 104 when determining the camera viewing angle.

[0082] In some embodiments, an item that has been successfully identified may be scanned to view specific wear, defects, or other aspects of the item. These item-specific scan results may be included in the description of the item or affect the condition of the item. In other embodiments, the item-specific scan results may be used to describe one or more images included in the release. Item-specific scans may be manually specified by the manufacturer, the online sales platform, or by buyer feedback.

[0083] For example, if it is determined that item 104 is a portable computing device such as a smart phone, the online selling platform may have determined that whether the screen is cracked is important to the buyer. Thus, computing device 130 may analyze the images captured by camera 206 to determine whether the screen of the item is cracked or otherwise damaged. If evidence of screen damage is found, the condition of the item may be downgraded. In addition, a picture of the crack may be included in the listing along with a description, such as how large the crack is, where the crack is located, etc.

[0084] In one embodiment, the robotic sales assistant 100 receives the seller-generated description 201 from the seller 107. The robotic sales assistant 100 can use the supplemental information 222 to determine whether the seller-generated description 201 is accurate. For example, the robotic sales assistant 100 can compare the model number included in the seller-generated description 201 with the model number included in the supplemental information 222. Similarly, the robotic sales assistant 100 can compare the claimed storage capacity with the storage capacity listed in the supplemental information 222.

[0085] Additionally or alternatively, the robotic sales assistant 100 can determine the accuracy of the supplemental information 222 by comparing with the measured values. For example, if a product brochure included in the supplemental information 222 lists the item size and weight, the robotic sales assistant 100 can compare the listed size and weight with the size measured by the laser distance measuring device 214 and the weight measured by the scale 204. Discrepancies can prevent the robotic sales assistant 100 from generating or publishing a release. Optionally, the robotic sales assistant 100 can report the discrepancy to the seller 107 and / or the company that will publish the release.

[0086] The item identifier 220 can also be used to find postings of similar items, i.e., items with the same item identifier 220. In other embodiments, similar items can be identified by comparing images of the current item with images from other postings, or by comparing measurements from sensors 204 to 214 with values ​​measured for other postings. Once identified, similar items can be used to determine price information, condition, etc. For example, the item identification engine 218 can analyze price data, sensor data, and data obtained from images of similar items. Trends such as a negative correlation between the price of an item and the range of values ​​captured by the UV camera 208, or a higher price for a particular color of the item can be used to estimate the affordability of the current item. In another embodiment, descriptions from postings of similar items can be used to generate a description of the current item.

[0087] Figure 2B 2 is a block diagram showing an example implementation 200 of aspects of a publishing bay 102 when capturing images 228A to 228F (collectively, "228") of an item 104A from multiple angles. As depicted, item 104A - a smart phone - rotates counterclockwise on turntable 202. As item 104A rotates, camera devices 206A and 206B capture a series of images 228A to 228F of item 104A. These images may be used in publishing, giving potential buyers a clear visual understanding of the item for sale.

[0088] Figure 2C1 is a block diagram illustrating aspects of the release compartment 102 when inserting the communication cable 213 embedded in the item handling arm 216 into the item 104. In some embodiments, the item handling arm 216 inserts the USB plug 233 of the communication cable 213 into the USB port 234 of the item 104A. The other end of the communication cable 213 can be plugged into the computing device 130, which can then be used as described above in conjunction with Figure 2A The item manipulation arm 216 can interact with the item 104A. Similarly, other types of communication interfaces are contemplated, including lightning cables, firewire cables, etc. Additionally or alternatively, the item manipulation arm 216 can insert a power cable into the item 104A so that an item that does not function under battery power can communicate with the computing device 130. Additionally or alternatively, in addition to scanning the item 104A using the communication cable 213, the item manipulation arm 216 can also be used to navigate a menu on the item 104A by manipulating a human-machine interface such as a touch screen, a keyboard, etc.

[0089] Figure 3A is a diagram illustrating aspects of a release 305A generated by the robotic sales assistant 100 according to one embodiment disclosed herein. Figure 3A Browser application 302 is depicted as having navigated to posting URL 304A of posting 305A. Posting 305A includes posting title 306A, captured image 308A, supplemental information 310A, pricing information 312A, description 314A, and shipping information 316A.

[0090] Although Figure 3A A publication 305A hosted in a web browser is depicted, but any other type of application is similarly contemplated. For example, a dedicated application may be used to navigate to and display a publication such as 305A.

[0091] The publication title 306A may be derived from the item identifier 220 and / or the supplemental information 222. For example, the publication title 306A may be derived from a product manual, a manufacturer's description, etc. Figure 3A , the posting title 306A describes a smart phone. Thus, in addition to a general description (e.g., "smart phone"), the robotic sales assistant 100 may also include a model (e.g., "Tornado Extreme"). However, different types of items may include different attributes in the title. For example, an antique or handmade item for which the manufacturer or model number is unknown may include a description of the materials used to create the item. The title 306A may include any number and type of attributes of the item 104, such as color, make, and model, etc. The title 306A may also include the condition of the item, such as "like new" or "used."

[0092] As discussed above, images 308A may include images 228 of item 104A taken from many different angles by camera(s) 206. Images 308A may also include images captured by UV camera 208 or IR camera 210, for example, UV images that reveal physiological fluids or mold, or IR images that indicate overheating or underheating conditions of electronic products operating outside of normal operating ranges. Images 308A may also include one or more images derived from supplemental information 310A, including images from a product manual associated with item 104.

[0093] Supplemental information 310A may include attributes associated with item 104. For example, supplemental information 310A may include a model number. The model number may be directly imprinted on item 104, or may be inferred from a serial number, a barcode, or other identifying information extracted from item 104. Based in part on the model number, supplemental information may also include the manual that originally came with item 104A. Supplemental information 310A may also include an estimated condition of item 104A derived from the age of the item, values ​​obtained by sensors 204 to 214, and the like.

[0094] The price information 312A may include a price suggested by the robotic sales assistant 100. The price may be estimated based in part on the original asking price of the item 104, the estimated condition of the item 104, a comparison to other instances of the item 104 that have been sold, etc. Additionally or alternatively, the robotic sales assistant 100 may suggest a price based on the prices of similar items sold within a defined time period, such as the prices of similar items that were recently sold. Similar items that are actively listed but not sold may also be used to suggest a price.

[0095] In some embodiments, the robotic sales assistant 100 may identify attributes of the item 104 that are "price-influencing" attributes—attributes that affect the selling price when mentioned in a posting. In some embodiments, the attributes of the item are physical characteristics of the item, such as the material from which the item is made, the condition of the item, etc. Attributes may also include non-physical characteristics of the item, such as brand, manufacturer, country of origin, etc. Attributes may be identified based on an analysis of postings of similar items—including analysis of titles, descriptions, keywords, images, etc.—to determine relevance to the final selling price. For example, an analysis of handbag postings may determine that handbags made of real leather have a higher final selling price than handbags made of faux leather. While maintaining an accurate description, the robotic sales assistant 100 may select attributes included in the posting title that are associated with a higher final selling price. At the same time, the robotic sales assistant 100 may minimize the impact of attributes associated with a lower selling price or avoid attributes associated with a lower selling price altogether.

[0096] Description 314A may include a text-based description of item 104. Text-based description 314A may be automatically generated based in part on supplemental information 310A, such as a manufacturer's description. In the case of an electronic item such as smartphone 104A, description 314A may list specifications, such as capacity, screen size, operating system version, etc.

[0097] Shipping information 316A may include a cost estimate based on packaging materials and shipping costs, which in turn may be derived from supplemental information 310 A. For example, supplemental information 310A may include product dimensions, weight, fragility, and other factors that determine packaging size and shipping costs.

[0098] Figure 3B is a diagram illustrating aspects of a posting 305B generated by the robotic sales assistant 100 according to one embodiment disclosed herein. The posting 305B includes a posting title 306B, a captured image 308B, supplemental information 310B, pricing information 312B, a description 314B, and shipping information 316B.

[0099] The publication title 306B may be derived from the item identifier 220 and / or the supplemental information 222. Figure 3B In the example, item 104B is a book, and thus title 306B includes the condition, title, and author of the book. However, this is just an example—any other supplemental information may be included in the publication title 306B, and different item types will include different portions of the supplemental information.

[0100] As discussed above, images 308B may include images 228 of item 104B taken from many different angles by camera(s) 206. Images 308B may also include images captured by UV camera 208 or IR camera 210, such as UV images that reveal physiological fluids or mold. Images 308B may also include one or more images derived from supplemental information 310B, including images provided by a publisher of item 104B.

[0101] Supplemental information 310B may include attributes associated with item 104B. For example, supplemental information 310B may include an ISBN number. The ISBN number may be directly imprinted on item 104, or may be inferred from identification information extracted from item 104B. Based in part on the ISBN number, supplemental information may also include a comment or review associated with item 104B, such as a comment or review created by a customer, a professional reviewer, etc. Supplemental information 310B may also include a condition of item 104B based on the values ​​obtained by sensors 206 to 214 as described above.

[0102] The price information 312B may include a price suggested by the robotic sales assistant 100. The price may be estimated based in part on the original asking price of the item 104B, an estimated condition of the item 104B, a comparison to other instances of the item 104B that have been sold, and the like.

[0103] Description 314B may include a text-based description of item 104B. Text-based description 314B may be automatically generated based in part on supplemental information 310A. In the case of a book, such as item 104B, description 314B may include a summary of the book provided by the publisher, extracted from a community-edited encyclopedia, etc. Description 314B may also include reviews, star ratings, etc. for item 104B.

[0104] Shipping information 316B may include a cost estimate based on packaging materials and shipping costs, which in turn may be derived from supplemental information 310B. For example, supplemental information 310B may include product size, weight, fragility, and other factors that determine packaging size and shipping costs.

[0105] Figure 4 400 for implementing some of the techniques disclosed herein. It will be appreciated by those of ordinary skill in the art that the operations of the methods disclosed herein are not necessarily presented in any particular order, and that it is feasible and contemplated to perform some or all of these operations in (one or more) alternative orders. For ease of description and illustration, the operations have been presented in the order demonstrated. The operations may be added, omitted, performed together, and / or performed simultaneously without departing from the scope of the appended claims.

[0106] It should also be understood that the method shown can end at any time and does not need to be executed as a whole. As defined herein, some or all of the operations and / or substantially equivalent operations in the method can be performed by executing computer-readable instructions included on a computer storage medium. As used in the description and claims, the term "computer-readable instructions" and its variations are widely used herein to include routines, applications, application modules, program modules, programs, components, data structures, algorithms, etc. Computer-readable instructions can be implemented on various system configurations, including single-processor systems or multi-processor systems, minicomputers, mainframe computers, personal computers, handheld computing devices, microprocessor-based programmable consumer electronics, combinations thereof, etc. Although the example routines described below are operated on a computing device, it is understood that the routines can be executed on any computing system, which can include multiple computers that work together to perform the operations disclosed herein.

[0107] Therefore, it should be understood that the logical operations described herein are implemented as (1) a series of computer-implemented actions or program modules running on a computing system such as those described herein and / or (2) interconnected machine logic circuits or circuit modules within a computing system. The implementation is a matter of choice depending on the performance and other requirements of the computing system. Therefore, the logical operations may be implemented in software, firmware, dedicated digital logic, and any combination thereof.

[0108] The routine 400 begins at operation 401, which illustrates receiving an item into a release compartment of a robotic sales assistant.

[0109] The routine 400 then proceeds to operation 403, which illustrates identifying the item using an image-based scanner.

[0110] The routine 400 then proceeds to operation 405, which illustrates retrieving supplemental information about the identified item.

[0111] The routine 400 then proceeds to operation 407, which generates image data of the item from the camera, wherein the viewing angle of the camera is based on the retrieved supplemental information.

[0112] Next, operation 409 illustrates generating a publication for the item, wherein the publication includes the image data and the supplemental information.

[0113] Figure 5 is a diagram illustrating aspects of a routine 500 for implementing some of the techniques disclosed herein.

[0114] The routine 500 begins at operation 501 , which illustrates receiving an indication that an item has been placed in a release compartment.

[0115] The routine 500 then proceeds to operation 503, which illustrates receiving a seller-generated description of the item.

[0116] The routine 500 then proceeds to operation 505, which illustrates causing the image-based scanner to determine the identity of the item.

[0117] The routine 500 then proceeds to operation 507, which illustrates retrieving supplemental information about the identified item.

[0118] Operation 509 illustrates generating a posting for the item when the seller-generated description of the item is consistent with the description of the item.

[0119] Figure 6 A computer capable of providing the functionality described herein is shown, such as, for example, configured to implement the above-described Figure 5An example computer architecture of a computing device that describes the functionality of the invention. Figure 6 The illustrated computer architecture 600 illustrates an architecture of a server computer or other type of computing device suitable for implementing the functionality described herein. The computer architecture 600 can be used to execute the various software components presented herein to implement the disclosed techniques.

[0120] Figure 6 The illustrated computer architecture 600 includes a central processing unit 602 ("CPU"), a system memory 604 including a random access memory 606 ("RAM") and a read-only memory ("ROM") 608, and a system bus 66 coupling the memory 604 to the CPU 602. Firmware, including basic routines such as those that help transfer information between elements within the computer architecture 600 during startup, is stored in the ROM 608. The computer architecture 600 also includes a mass storage device 612 for storing an operating system 614, other data such as the supplemental information 222, and one or more executable programs such as the item identification engine 218.

[0121] The mass storage device 612 is connected to the bus 66 through a mass storage controller ( Figure 6 The mass storage device 612 and its associated computer-readable media provide non-volatile storage for the computer architecture 600. Although the description of computer-readable media contained herein refers to mass storage devices such as solid-state drives, hard disks, or optical drives, those skilled in the art will appreciate that computer-readable media can be any available computer storage media or communication media that can be accessed by the computer architecture 600.

[0122] Communication media includes computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and includes any transmission media. The term "modulated data signal" refers to a signal that has one or more of its characteristics changed or set in a manner that encodes information in the signal. By way of example and not limitation, communication media include: wired media such as a wired network or a direct wired connection; and wireless media such as acoustic, radio frequency, infrared and other wireless media. Any combination of the above should also be included within the scope of computer readable media.

[0123] By way of example and not limitation, computer readable storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. For example, computer media include, but are not limited to: RAM, ROM, EPROM, EEPROM, flash memory or other solid state storage technology, CD-ROM, digital versatile disk ("DVD"), HD-DVD, BLU-RAY or other optical storage devices, cassettes, magnetic tape, magnetic disk storage devices or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by the computer architecture 600. For the purposes of the claims, the phrases "computer storage medium", "computer readable storage medium" and variations thereof do not by themselves include waves, signals and / or other transient and / or intangible communication media.

[0124] According to various implementations, the computer architecture 600 can be used to communicate with the network 650 and / or another network ( Figure 6 The computing device implementing the computer architecture 600 can be connected to the network 650 through a network interface unit 616 connected to the bus 66. It should be understood that the network interface unit 616 can also be used to connect to other types of networks and remote computer systems.

[0125] The computer architecture 600 may also include a computer for receiving and processing data from many other devices including a keyboard, a mouse, or an electronic pen ( Figure 6 Similarly, the input / output controller 618 can send data to a display screen, a printer, or other type of output device (not shown). Figure 6 (not shown) provides an output.

[0126] It should be understood that the software components described herein can convert CPU 602 and the entire computer architecture 600 from a general-purpose computing system to a special-purpose computing system customized to facilitate the functions presented herein when loaded into CPU 602 and executed. CPU 602 can be composed of any number of transistors or other discrete circuit elements, which can assume any number of states individually or collectively. More specifically, CPU 602 can operate as a finite state machine in response to executable instructions contained in the software modules disclosed herein. These computer executable instructions can convert CPU 602 by specifying how CPU 602 changes between states, thereby converting transistors or other discrete hardware elements that constitute CPU 602.

[0127] Encoding the software modules presented herein may also convert the physical structure of the computer-readable medium presented herein. In different implementations of this description, the specific conversion of the physical structure may depend on various factors. Examples of such factors may include, but are not limited to, the technology used to implement the computer-readable medium, whether the computer-readable medium is characterized as a primary storage device or an auxiliary storage device, etc. If the computer-readable medium is implemented as a semiconductor-based memory, the software disclosed herein may be encoded on the computer-readable medium by converting the physical state of the semiconductor memory. For example, the software may convert the state of transistors, capacitors, or other discrete circuit elements that constitute the semiconductor memory. The software may also convert the physical state of such components to store data thereon.

[0128] As another example, magnetic or optical technology can be used to implement the computer-readable medium disclosed herein. In such an implementation, the software presented herein can convert the physical state of the magnetic medium or optical medium when the software is encoded in the magnetic medium or optical medium. These conversions can include changing the magnetic characteristics of the position in a given magnetic medium. These conversions can also include changing the physical characteristics or features of the position in a given optical medium to change the optical characteristics of these positions. Without departing from the scope and spirit of this description, other conversions of physical media can be performed, and the aforementioned examples are only provided to facilitate this discussion.

[0129] In view of the above, it should be understood that many types of physical transformations occur in the computer architecture 600 to store and execute the software components presented herein. It should also be understood that the computer architecture 600 may include other types of computing devices, including handheld computers, embedded computer systems, personal digital assistants, and other types of computing devices known to those skilled in the art.

[0130] It is also contemplated that the computer architecture 600 may not include Figure 6 All components shown may include those not shown in Figure 6 Other components explicitly shown in the Figure 6 . For example and without limitation, the techniques disclosed herein may be used with multiple CPUs for improving performance through parallelization, graphics processing units (“GPUs”) for faster computations, and / or tensor processing units (“TPUs”). The term “processor” as used herein includes CPUs, GPUs, TPUs, and other types of processors.

[0131] Figure 7 It is shown that the above-mentioned FIG. 1 to FIG. Figure 7An example computing environment for describing the techniques and processes. In various examples, the computing environment includes a host system 702. In various examples, the host system 702 operates on, in communication with, or as part of a network 704.

[0132] The network 704 may be or may include various access networks. For example, one or more client devices 706(1)...706(N) may communicate with the host system 702 via the network 704 and / or other connections. The host system 702 and / or the client devices may include, but are not limited to, any of the following various devices: the various devices include portable devices or fixed devices such as server computers, smart phones, mobile phones, personal digital assistants (PDAs), e-book devices, laptop computers, desktop computers, tablet computers, portable computers, game consoles, personal media player devices, or any other electronic devices.

[0133] According to various implementations, the functionality of the host system 702 may be provided by one or more servers executing as part of or in communication with the network 704. The servers may host various services, virtual machines, portals, and / or other resources. For example, one or more portals, websites, and / or other information may be hosted or accessed.

[0134] The host system 702 may include processor(s) 708 and memory 710. The memory 710 may include an operating system 712, application(s) 714, and / or a file system 716. In addition, the memory 710 may include performance specifications, item attributes, images, and other information as described above with respect to FIGS. Figure 7 Other data generated and consumed as described.

[0135] (One or more) processors 708 may be a single processing unit or multiple units, each of which may include multiple different processing units. (One or more) processors may include microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units (CPUs), graphics processing units (GPUs), security processors, etc. Alternatively or additionally, some or all of the techniques described herein may be performed at least in part by one or more hardware logic components. For example, but not limited to, illustrative types of hardware logic components that may be used include field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), state machines, complex programmable logic devices (CPLDs), other logic circuits, systems on chip (SoCs), and / or any other device that performs operations based on instructions. Among other capabilities, (one or more) processors may be configured to obtain and execute computer-readable instructions stored in memory 710.

[0136] Memory 710 may include one or a combination of computer-readable media. As used herein, "computer-readable media" includes both computer storage media and communication media.

[0137] Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media include, but are not limited to: phase change memory (PCM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), flash memory or other memory technology, compact disk ROM (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store information for access by a computing device.

[0138] In contrast, communication media includes computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave. As defined herein, computer storage media does not include communication media.

[0139] Host system 702 may communicate over network 704 via network interface 718. Network interface 718 may include various types of network hardware and software for supporting communications between two or more devices.

[0140] The present technology may involve operations that occur in one or more machines. As used herein, a "machine" refers to physical data storage and processing hardware that is programmed with instructions to perform specialized computing operations. It should be understood that two or more different machines may share hardware components. For example, the same integrated circuit may be part of two or more different machines.

[0141] It should be understood that the method described herein can be terminated at any time and does not need to be executed as a whole. Some or all of the operations of the method described herein and / or substantially equivalent operations can be performed by executing computer-readable instructions as defined below included on a computer storage medium. As used in the description and claims, the term "computer-readable instructions" and variations thereof are widely used herein to include routines, applications, application modules, program modules, programs, components, data structures, algorithms, etc. Computer-readable instructions can be implemented on various system configurations, including single-processor systems or multi-processor systems, minicomputers, mainframe computers, personal computers, handheld computing devices, programmable consumer electronics based on microprocessors, combinations thereof, etc.

[0142] Therefore, it should be understood that the logical operations described herein are implemented as (1) a series of computer-implemented actions or program modules running on a computing system and / or (2) interconnected machine logic circuits or circuit modules within a computing system. The implementation is a matter of choice depending on the performance and other requirements of the computing system. Therefore, the logical operations described herein are variously referred to as states, operations, structural devices, actions, or modules. These operations, structural devices, actions, and modules can be implemented in software, firmware, dedicated digital logic, and any combination thereof.

[0143] As described herein, in conjunction with the accompanying drawings described herein, the operation of the routine is described herein as being implemented at least in part by applications, components and / or circuits. Although the following description relates to the components of the specified drawings, it is understood that the operation of the routine can also be implemented in many other ways. For example, the routine can be implemented at least in part by a processor or multiple processors of a computer processor or other computer. In addition, alternatively or additionally, one or more operations of the routine can be implemented at least in part by a computer working alone or in combination with other software modules.

[0144] For example, the operation of a routine is described herein as being implemented at least in part by applications, components, and / or circuits, which are collectively referred to herein as modules. In some configurations, a module may be a dynamic link library (DLL), a static link library, a function generated by an application programming interface (API), a compiled program, an interpreter, a script, or any other executable instruction set. Data and / or modules, such as those disclosed herein, may be stored in one or more memory components in a data structure. Data may be retrieved from a data structure by addressing a link or reference to the data structure.

[0145] Finally, although the various techniques presented herein have been described in language specific to structural features and / or methodological acts, it should be understood that the subject matter defined in the accompanying representations is not necessarily limited to the specific features or acts described. Rather, these specific features and acts are disclosed as example forms of implementing the claimed subject matter.

Claims

1. A computer-operated vehicle for automatically generating a posting of an item for sale, the vehicle comprising: a temporary storage compartment for placing said items; a release bay accessible by an automatic door, comprising one or more image-based sensors and one or more camera devices located within the release bay, and wherein the one or more image-based sensors are configured to identify items from the staging bay that are placed within the release bay; Storage devices for items; wherein the computer-operated vehicle is configured to automatically generate a posting for the item by executing a routine comprising the following instructions: receiving the article from the temporary storage compartment in the release compartment; identifying the item using the one or more image-based sensors within the release compartment; Retrieving supplemental information about the identified object based on the identification result of the object, wherein the supplemental information can identify the size and shape of the object and at least one performance specification; generating image data of the item from the one or more cameras within the issuance compartment, wherein a zoom level and an angle and distance from the item of the one or more cameras are based on the size and shape of the item identified by the supplemental information; generating a publication for the article, the publication including the image data and the supplemental information; and In response to generating a release for the item, transferring the item from the release compartment to the item storage device to await unloading to a warehouse, delivery to a buyer, or packaging for transfer to a packaging delivery service; The instructions further include: autonomously inserting a communications cable into said article; retrieving additional supplemental information about the item via the communications cable; and The additional supplemental information about the item is included in the publication.

2. The computer operated vehicle of claim 1, wherein: The supplemental information is retrieved based on an identifier encoded in a bar code on the item.

3. The computer operated vehicle of claim 1, wherein: The release compartment includes a turntable on which the items are placed, and wherein the one or more camera devices take pictures of the items from different perspectives as the turntable rotates the items.

4. The computer operated vehicle of claim 3, wherein: A laser distance measuring device determines at least one of a physical size or shape of the article as the turntable rotates the article.

5. The computer operated vehicle of claim 4, wherein: Custom packaging is created to ship the item based on the item's physical size or shape.

6. The computer operated vehicle of claim 1, wherein: A laser distance measuring device mounted on a gimbal moves in three dimensions about the item to measure a second size of the item, and wherein the size of the item is compared to the second size of the item to verify the accuracy of the publication.

7. A computing system for a vehicle for automatically generating postings of items for sale, the vehicle comprising a staging compartment, a posting compartment accessible by an automatic door, and an item storage device, the posting compartment comprising one or more image-based sensors located within the posting compartment, and the one or more image-based sensors being configured to identify items from the staging compartment placed within the posting compartment, the computing system comprising: one or more processors; as well as A computer-readable storage medium having stored thereon computer-executable instructions for automatically generating a release of the item, the computer-executable instructions, when executed by the processor, causing the processor to: receiving an indication that the item from the staging compartment has been placed in the release compartment; identifying the item using the one or more image-based sensors within the release compartment; Retrieving supplemental information about the identified object based on the identification result of the object, wherein the supplemental information can identify the size and shape of the object and at least one performance specification; generating image data of the item from the one or more cameras within the issuance compartment, wherein a zoom level and an angle and distance from the item of the one or more cameras are based on the size and shape of the item identified by the supplemental information; generating a publication for the article, the publication including the image data and the supplemental information; and In response to generating a release for the item, transferring the item from the release compartment to the item storage device to await unloading to a warehouse, delivery to a buyer, or packaging for transfer to a packaging delivery service; The computer executable instructions further include: autonomously inserting a communications cable into said article; retrieving additional supplemental information about the item via the communications cable; and The additional supplemental information about the item is included in the publication.

8. A computer-readable storage medium having stored thereon computer-executable instructions for automatically generating a posting of an item for sale, the computer-executable instructions, when executed by a processor of a computing device, causing the computing device to: receiving an indication that an item from a staging compartment of a vehicle for automatically generating a posting of an item for sale is placed in a posting compartment of an autonomous sales unit, wherein, The vehicle includes the staging compartment, a release compartment accessible with an automated door, and an item storage device, the release compartment including one or more image-based sensors located within the release compartment, and the one or more image-based sensors are configured to identify an item from the staging compartment placed within the release compartment; identifying the item using the one or more image-based sensors located within the release compartment; Retrieving supplemental information about the identified object based on the identification result of the object, wherein the supplemental information can identify the size and shape of the object and at least one performance specification; generating image data of the item from the one or more cameras within the issuance compartment, wherein a zoom level and an angle and distance from the item of the one or more cameras are based on the size and shape of the item identified by the supplemental information; generating a publication for the article, the publication including the image data and the supplemental information; and In response to generating a release for the item, transferring the item from the release compartment to the item storage device to await unloading to a warehouse, delivery to a buyer, or packaging for transfer to a packaging delivery service; The computer executable instructions further include: autonomously inserting a communications cable into said article; retrieving additional supplemental information about the item via the communications cable; and The additional supplemental information about the item is included in the publication.

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