This application is related to U.S. patent application Ser. No. 14/815,110, titled “Operator Identification and Performance Tracking”, filed concurrently with this application, incorporated herein by reference.
This invention relates to robotic navigation using semantic mapping and more particularly to robotic navigation using semantic mapping to navigate robots throughout a warehouse in robot-assisted product order-fulfillment systems.
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.
Robot assisted order-fulfillment systems have been used to increase efficiency and productivity. However, there is still a need to further increase efficiency in such systems.
In one aspect, the invention features a method for performing tasks on items located in a space using a robot, the items being located proximate fiducial markers, each fiducial marker having a fiducial identification. The method comprises receiving an order to perform a task on at least one item and determining the fiducial identification associated with the at least one item. The method also includes obtaining, using the fiducial identification of the at least one item, a set of coordinates representing a position of the fiducial marker with the determined fiducial identification, in a coordinate system defined by the space, The method further includes navigating the robot to the coordinates of the fiducial marker associated with said determined fiducial identification.
In other aspects of the invention one or more of the following features may be included. The method may further include communicating with a human operator to perform the task on the at least one item, wherein the task includes one of retrieving the at least one item and placing it on the robot or removing the at least one item from the robot and storing it proximate the fiducial marker. The space may be a warehouse containing a plurality of items stored in a plurality of containers dispersed throughout the warehouse. Each fiducial marker may be associated with and located proximate to one or more of the containers. The step of determining the fiducial identification may include establishing a fiducial identification system based on a physical layout of the containers dispersed throughout the warehouse and associating each container to a fiducial identification corresponding to the physical location of the container in the warehouse. The step of associating each container to a fiducial identification may further include linking the fiducial identification of the container to the items. The step of determining the set of coordinates representing a position of the fiducial marker with the determined fiducial identification may include correlating the determined fiducial identification with its corresponding fiducial marker and retrieving a set of coordinates representing the position of said fiducial marker in the coordinate system of the warehouse. Retrieving the set of coordinates representing the position of said fiducial marker may include determining a pose for the fiducial marker within the warehouse and the step of navigating may include propelling the robot to the pose without using intermediate fiducial markers to guide the robot to the fiducial marker correlated to the determined fiducial identification. The step of navigating may further include using a predetermined map of the warehouse including a pose for each fiducial marker to guide the robot to the fiducial marker.
In another aspect of this invention there is a robot configured to perform tasks on items located in a space, the items being located proximate fiducial markers, each fiducial marker having a fiducial identification. The robot includes a processor configured to determine a fiducial identification associated with at least one item on which the robot is to perform a task. The robot is further configured to obtain, using the fiducial identification of the at least one item, a set of coordinates representing a position of the fiducial marker with the determined fiducial identification, in a coordinate system defined by the space. There is a navigation system configured to navigate the robot to the coordinates of the fiducial marker associated with the determined fiducial identification.
In other aspects of the invention one or more of the following features may be included. The robot may include an interface device configured to communicate with a human operator to perform the task on the at least one item. The task may include one of retrieving the at least one item and placing it on the robot or removing the at least one item from the robot and storing it proximate the fiducial marker. The space may be a warehouse containing a plurality of items stored in a plurality of containers dispersed throughout the warehouse. Each fiducial marker may be associated with and located proximate to one or more of the containers. Each container in the warehouse may be associated to a fiducial identification corresponding to the physical location of the container in the warehouse. The fiducial identification of the container may be linked to the items stored in the containers. The processor may further be configured to correlate the determined fiducial identification with its corresponding fiducial marker and retrieve a set of coordinates representing the position of said fiducial marker in the coordinate system of the warehouse. The processor may further be configured to determine a pose for the fiducial marker within the warehouse and the navigation system may be configured to propel the robot to the pose without using intermediate fiducial markers to guide the robot to the fiducial marker correlated to the determined fiducial identification. The navigation system may include a map of the warehouse with a pose for each fiducial marker.
These and other features of the invention will be apparent from the following detailed description and the accompanying figures, in which:
Referring to
A typical robot 18, shown in
While the description provided herein is focused on picking items from bin locations in the warehouse to fulfill an order for shipment to a customer, the system is equally applicable to the storage or placing of items received into the warehouse in bin locations throughout the warehouse for later retrieval and shipment to a customer. The invention could also be utilized with other standard tasks associated with such a warehouse system, such as, consolidation of items, counting of items, verification, and inspection.
An upper surface 36 of the base 20 features a coupling 38 that engages any one of a plurality of interchangeable armatures 40, one of which is shown in
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 on 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, 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. shown in
Upon reaching the correct location, 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 packing 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 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 of the robots 18 navigates the warehouse and builds 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 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, ω) 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,
Item specific information, such as SKU number and bin location, obtained by the warehouse management system 15, 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.
Number | Name | Date | Kind |
---|---|---|---|
3553438 | Blitz et al. | Jan 1971 | A |
3971917 | Maddox et al. | Jul 1976 | A |
5156513 | Galan et al. | Oct 1992 | A |
5521843 | Hashimi et al. | May 1996 | A |
6064749 | Hirota et al. | May 2000 | A |
6435407 | Fiordelisi | Aug 2002 | B1 |
6681031 | Cohen et al. | Jan 2004 | B2 |
6762681 | Danelski | Jul 2004 | B1 |
6775588 | Peck | Aug 2004 | B1 |
7077318 | Venema et al. | Jul 2006 | B2 |
7231063 | Naimark et al. | Jun 2007 | B2 |
7693654 | Dietsch et al. | Apr 2010 | B1 |
7693757 | Zimmerman | Apr 2010 | B2 |
7774243 | Antony et al. | Aug 2010 | B1 |
8224024 | Foxlin et al. | Jul 2012 | B2 |
8381982 | Kunzig et al. | Feb 2013 | B2 |
8731708 | Shakes et al. | May 2014 | B2 |
8746631 | Hashimoto et al. | Jun 2014 | B2 |
8751035 | Janét | Jun 2014 | B2 |
8827619 | Schäfer | Sep 2014 | B2 |
8862395 | Richardson | Oct 2014 | B2 |
8874261 | Hein et al. | Oct 2014 | B2 |
8892241 | Weiss | Nov 2014 | B2 |
8965560 | Mathi et al. | Feb 2015 | B2 |
8965561 | Jacobus et al. | Feb 2015 | B2 |
9002510 | Chudy et al. | Apr 2015 | B2 |
9463927 | Theobald | Oct 2016 | B1 |
20060293810 | Nakamoto | Dec 2006 | A1 |
20070050080 | Peck | Mar 2007 | A1 |
20070081695 | Foxlin et al. | Apr 2007 | A1 |
20070124077 | Hedlund, Jr. | May 2007 | A1 |
20080077511 | Zimmerman | Mar 2008 | A1 |
20090030551 | Hein et al. | Jan 2009 | A1 |
20100045701 | Scott et al. | Feb 2010 | A1 |
20100057245 | Hironaka et al. | Mar 2010 | A1 |
20100296908 | Ko | Nov 2010 | A1 |
20110010023 | Kunzig et al. | Jan 2011 | A1 |
20110121068 | Emanuel et al. | May 2011 | A1 |
20110200420 | Driskill et al. | Aug 2011 | A1 |
20110228080 | Ding et al. | Sep 2011 | A1 |
20110301994 | Tieman | Dec 2011 | A1 |
20120191272 | Andersen | Jul 2012 | A1 |
20120197519 | Richardson | Aug 2012 | A1 |
20120265054 | Olson | Oct 2012 | A1 |
20120330458 | Weiss | Dec 2012 | A1 |
20130073076 | Mathi et al. | Mar 2013 | A1 |
20130204430 | Davey et al. | Aug 2013 | A1 |
20130231779 | Purkayastha et al. | Sep 2013 | A1 |
20130312371 | Ambrose | Nov 2013 | A1 |
20130317642 | Asaria | Nov 2013 | A1 |
20140022281 | Georgeson | Jan 2014 | A1 |
20140058612 | Wong et al. | Feb 2014 | A1 |
20140058634 | Wong et al. | Feb 2014 | A1 |
20140074342 | Wong | Mar 2014 | A1 |
20140100693 | Fong et al. | Apr 2014 | A1 |
20140257553 | Shakes et al. | Sep 2014 | A1 |
20140277691 | Jacobus | Sep 2014 | A1 |
20140278097 | Khorsheed et al. | Sep 2014 | A1 |
20140350725 | LaFary et al. | Nov 2014 | A1 |
20150012396 | Puerini et al. | Jan 2015 | A1 |
20150012456 | Elberbaum | Jan 2015 | A1 |
20150073586 | Weiss | Mar 2015 | A1 |
20150073589 | Khodl et al. | Mar 2015 | A1 |
20150081088 | Lyon et al. | Mar 2015 | A1 |
Number | Date | Country |
---|---|---|
2255971 | Dec 1993 | GB |
2679410 | Nov 1997 | JP |
3633679 | Mar 2005 | JP |
3673441 | Jul 2005 | JP |
WO9854593 | Dec 1998 | WO |
WO2014090684 | Jun 2014 | WO |
Entry |
---|
Anonymous: “Pose (computer vision)—Wikipedia, the free encyclopedia”, Jul. 2, 2015, XP055304489,Retrieved from the Internet: URL: https://en.wikipedia.org/w/index.php?title=Pose—(computer—vision)&olddid-669666788 [retrieved on Sep. 21, 2016]. |
Anonymous: “Simultaneous localization and mapping—Wikipedia, the free encyclopedia”, (computer vision)—Wikipedia, the free encyclopedia, Jul. 17, 2015, XP055304592, Retrieved from the Internet: URL: https://en.wikipedia.org/w/index.php?title=Simultaneous—localization—and—mapping&oldid=671889899 [retrieved on Sep. 21, 2016]. |
International Search Report with Written Opinion, dated Sep. 30, 2016, received in international patent application No. PCT/US2016/044985, 13 pgs. |
Number | Date | Country | |
---|---|---|---|
20170029213 A1 | Feb 2017 | US |