Mobile robotic devices have minimized the human effort involved in performing everyday tasks. For example, automatic cleaning devices help maintaining and cleaning surfaces, such as hardwood floors, carpet and the like. Mobile robotic devices are useful, but location detection can be a challenge for the operation of such devices.
Before the present methods are described, it is to be understood that this invention is not limited to the particular systems, methodologies or protocols described, as these may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present disclosure which will be limited only by the appended claims.
It must be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural reference unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art. As used herein, the term “comprising” means “including, but not limited to.”
In an embodiment, a method of cleaning an area using an automatic cleaning device may include: by a video camera, collecting visual information associated with an area in which a mobile robotic device is located; receiving information from the video camera, wherein the information comprises a value associated with a detected color in the area; comparing the value associated with the detected color to a value of a requested color; determining whether the value associated with the detected color is within a tolerance range of the value of the requested color; if the value associated with the detected color is within a tolerance range of the value of the requested color, accepting the color; and using the received information to adjust a position of the mobile robotic device in the area.
In an embodiment, the method also includes using one or more sensors to receive positional information for the mobile robotic device. In this embodiment, using the received information to adjust a position of the mobile robotic device in the area comprises comparing the positional information and the information received from the video camera to a digital representation of a map. The map may be used to determine a current position of the mobile robotic device. The method may then include determining which of the received information has a least amount of error as compared to the current position, and causing the mobile robotic device to adjust its position based on the information that has the least amount of error.
The received information also may include one or more of the following: coordinates associated with a substantially center portion of the area; coordinates associated with one or more corners of a rectangle that surrounds the area; or a number of pixels of the detected color within the area.
In some embodiments, using the received information to adjust a position of the mobile robotic device may include adjusting a path of the mobile robotic device based on the received information in response to an amount of error associated with the received information as compared to the position being less than an amount of error associated with the received position data as compared to the position. In other embodiments, using the received information to adjust a position of the mobile robotic device may include: determining an estimated location of the mobile robotic device; using the received information to determine an actual location of the mobile robotic device; and if the estimated location differs from the actual location, moving the mobile robotic device to the estimated location.
In some embodiments, the mobile robotic device may include an automated cleaning device. If so, the cleaning device may be caused to clean a surface of the area as the automated cleaning device adjusts its position. This may include determining one or more characteristics associated with the surface, determining a cleaning method based on the determined one or more characteristics, and causing the automated cleaning device to apply the cleaning method to the surface.
Aspects, features, benefits and advantages of the present invention will be apparent with regard to the following description and accompanying drawings, of which:
In an embodiment, the video camera 105 may be a color video camera, a black and white video camera and/or the like. In an embodiment, the video camera 105 may be mounted on a front portion of a mobile robotic device 100. In an alternate embodiment, the video camera 105 may be mounted on a rear portion, a side portion or other portion of the mobile robotic device 100. The video camera 105 may include a processing device, a computer-readable storage medium and/or the like. In an embodiment, the video camera 105 may be in communication with the mobile robotic device 100 and/or one or more external processing devices, computer-readable storage mediums and/or the like. For example, the video camera 105 may collect information about the mobile robotic device's surroundings such as coordinates, navigational information, visual information and/or the like. The video camera 105 may provide this information to the mobile robotic device 100.
In an embodiment, the video camera 105 may be a CMUcam3. The CMUcam3 is an ARM7TDMI-based programmable embedded computer vision sensor developed by Carnegie Mellon University. Additional and/or alternate video cameras may be used within the scope of this disclosure.
In an embodiment, the mobile robotic device may receive 200 information regarding an edge from the video camera. The information may include values associated with the slope, the intercept and/or the error of a line detected by the video camera. For example, the slope, intercept and/or error associated with a substantially straight line from an image of a surface, such as a ground surface, a floor surface or other surface over which the mobile robotic device is travelling may be provided to the mobile robotic device. In an embodiment, the video camera may repetitively send updated information to the mobile robotic device. For example, the video camera may send the mobile robotic device updated slope values, intercept values and/or error values associated with a detected line several times per second.
In an embodiment, a mobile robotic device may use this information to determine its position relative to the detected edge. For example, a mobile robotic device may compare information about its current position, such as its coordinates, heading and/or the like, with information received from the video camera regarding the edge. The mobile robotic device may use this comparison to determine its position relative to the edge, its distance away from the edge and/or the like.
In an embodiment, a mobile robotic device may detect an edge located in the direction of the mobile robotic device's movement. For example, a mobile robotic device may detect an edge in front of the mobile robotic device when the mobile robotic device is moving forward. A mobile robotic device may detect an edge that is substantially perpendicular to its movement. For example, a mobile robotic device may detect an edge associated with a wall or other barrier that the mobile robotic device is approaching. In an embodiment, a mobile robotic device may adjust its motion based on its proximity to a detected edge. For example, a mobile robotic device may turn itself around or otherwise change its course when it comes within two feet of the detected edge. Additional and/or alternate proximities may be used within the scope of this disclosure.
In an embodiment, the mobile robotic device may determine 205 whether to use any of the information received from the video camera to adjust its position. For example, the mobile robotic device may receive 210 positional information from one or more sensors, such as sonar, radar and/or the like. The mobile robotic device may compare 215 the information that it receives from its sensors and the information that it receives from the video camera to information from a map of an area or environment in which the mobile robotic device is navigating.
In an embodiment, a map may be generated by the mobile robotic device and/or another computing device during the mobile robotic device's first navigation of the area. For example, the mobile robotic device may be manually controlled through an area during which time the mobile robotic device may generate and store a map of the navigated area. In an embodiment, the mobile robotic device may compare 215 the information it receives 210 from its sensors and the information it receives from the video camera to the digital representation of the map to determine which information to use. In an embodiment, the mobile robotic device may use the information that has the least amount of error as compared to the mobile robotic device's current position. For example, a mobile robotic device may determine a current position using a map. It may compare the information received from its sensor and the information it receives from its video camera to determine which information has the least amount of error relative to its current position. The mobile robotic device may adjust its position based on the information associated with the least amount of error.
In an embodiment, the mobile robotic device may use the information associated with an edge and its determined position to navigate 220 a path. In an embodiment, the mobile robotic device may navigate 220 a path relative to the edge. For example, the mobile robotic device may navigate 220 a path that begins at the determined position and that runs parallel to the edge. Alternatively, the mobile robotic device may navigate 220 a path that begins at the determined position and that is not parallel to the edge.
In an embodiment, the mobile robotic device may navigate 220 a path such that the edge is located a certain distance from a reference point on the mobile robotic device. The reference point may be a side portion, a front portion, a back portion and/or the like of the mobile robotic device. For example, a mobile robotic device may use a detected line as a side registration by tracking the line on the right or left side of the mobile robotic device.
In an embodiment, a mobile robotic device may include an automatic cleaning device. An automatic cleaning device may be a mobile robotic device that can automatically navigate and clean surfaces, such as floors.
As described above with respect to a mobile robotic device, an automatic cleaning device may receive 300 information regarding an edge from the video camera. The information may include values associated with the slope, the intercept and/or the error of a line detected by the video camera.
In an embodiment, an automatic cleaning device may use this received information to determine its position relative to the detected edge. For example, an automatic cleaning device may compare information about its current position, such as its coordinates, heading and/or the like, with information received from the video camera regarding the edge.
In an embodiment, the automatic cleaning device may determine 305 whether to use any of the information received from the video camera to adjust its position. For example, the automatic cleaning device may receive 310 positional information from one or more sensors, such as sonar, radar and/or the like. The automatic device may compare 315 the information that it receives from its sensors and the information that it receives from the video camera to information from a map of an area in which the automatic cleaning device is navigating.
In an embodiment, the automatic cleaning device may compare 315 the information it receives 310 from its sensors and the information it receives from the video camera to the digital representation of the map to determine which information to use. In an embodiment, the automatic cleaning device may use the information that has the least amount of error as compared to the automatic cleaning device's current position. For example, an automatic cleaning device may determine a current position using a map. It may compare the information received from its sensor and the information it receives from its video camera to determine which information has the least amount of error relative to its current position. The automatic cleaning device may adjust its position based on the information associated with the least amount of error.
In an embodiment, the automatic cleaning device may use the information associated with an edge and its determined position to navigate 320 a path. The automatic cleaning device may navigate 320 a path relative to the edge. For example, the automatic cleaning device may navigate 320 a path that begins at the determined position and that runs parallel to the edge. In an embodiment, the automatic cleaning device may navigate 320 the path such that the edge is located a certain distance from a reference point on the automatic cleaning device. The reference point may be a side portion, a front portion, a back portion and/or the like of the automatic cleaning device. For example, an automatic cleaning device may use a detected line as a side registration by tracking the line on the right or left side of the automatic cleaning device.
In an embodiment, the automatic cleaning device may clean 325 at least a portion of its navigated path. For example, an automatic cleaning device may be able to determine one or more characteristics corresponding to its determined position. A characteristic may include, for example, a floor type, such as hard wood, tile, carpet and/or the like. A characteristic may include whether the position is in a high-traffic area, a low-traffic area and/or the like. In an embodiment, an automatic cleaning device may determine an appropriate cleaning method based on the determined characteristics. For example, the automatic cleaning device may vacuum a carpeted area, scrub and/or wax a hardwood or tile area and/or the like.
In an embodiment, a mobile robotic device may navigate its surroundings based on its location relative to an area of a particular color. An area may be a surface area, an item, a landmark and/or the like. For example, a mobile robotic device may navigate an area based on its relative position to a green chair located in a room.
In an embodiment, the mobile robotic device may receive 505 information from the video camera. For example, the mobile robotic device may receive 505 from the video camera coordinates associated with a substantially central portion of an area corresponding to the specified color. The mobile robotic device may also receive 505 coordinates of one or more corners of a rectangle that encompasses the detected area. For example, the video camera may send the mobile robotic device coordinates of the corners of a bounding box that is just large enough to completely encompass the detected area. In an embodiment, the mobile robotic device may receive a number of pixels of the color that were detected in the area.
In an embodiment, the mobile robotic device may receive 505 from the video camera a numerical value associated with a detected color and/or an associated tolerance range. For example, each color that is detected by the video camera may be assigned a numerical value. The numerical value associated with a detected color may be compared to a numerical value associated with the requested color. If the numerical value associated with the detected color is within a tolerance range (i.e., the numerical value associated with the requested color +/− the tolerance value), the detected color may be accepted. The mobile robotic device may receive from the video camera the value of the detected color and/or the tolerance range.
In an embodiment, the mobile robotic device may determine 510 whether to use any of the information received from the video camera in navigating its path. For example, the mobile robotic device may receive 515 positional information from one or more sensors, such as sonar, radar and/or the like. In an embodiment, the mobile robotic device may compare 520 the information that it receives from its sensors and the information that it receives from the video camera to information from a map of an area in which the mobile robotic device is navigating.
In an embodiment, a map may be generated by the mobile robotic device and/or another computing device during the mobile robotic device's first navigation of the area. For example, the mobile robotic device may be manually controlled through an area during which time the mobile robotic device may generate and store a map of the navigated area. In an alternate embodiment, a map of an area may be generated manually. For example, a map may be generated by a user and a digital representation of the map may be stored electronically.
In an embodiment, the mobile robotic device may compare 520 the information it receives 515 from its sensors and the information it receives from the video camera to the digital representation of the map to determine which information to use. In an embodiment, the mobile robotic device may use the information that has the least amount of error as compared to the mobile robotic device's current position. For example, a mobile robotic device may determine a current position using a map. It may compare the information received from its sensor and the information it receives from its video camera to determine which information has the least amount of error relative to its current position. The mobile robotic device may adjust its position based on the information associated with the least amount of error.
In an embodiment, the mobile robotic device may adjust 525 its position based on the most accurate information. The mobile robotic device may use the information to adjust 525 its position, heading and/or the like. For example, an estimated position of the mobile robotic device may be determined. The estimated position may include coordinates, a heading and/or the like. In an embodiment, an actual position may be determined based on the information associated with the detected area that is received by the mobile robotic device. The estimated position may be compared to the actual position, and the mobile robotic device may adjust 525 its position to compensate for any positional error that may exist. For example, the mobile robotic device may navigate from its actual position to the estimated position.
In an embodiment, the automatic cleaning device may receive 605 information from the video camera. For example, the automatic cleaning device may receive 605 from the video camera coordinates associated with a substantially central portion of an area corresponding to the specified color. The automatic cleaning device may also receive 605 coordinates of one or more corners of a rectangle that encompasses the detected area. In an embodiment, the automatic cleaning device may receive a number of pixels of the color that were detected in the area.
In an embodiment, the automatic cleaning device may receive 605 from the video camera a numerical value associated with a detected color and/or an associated tolerance range. For example, each color that is detected by the video camera may be assigned a numerical value. The numerical value associated with a detected color may be compared to a numerical value associated with the requested color. If the numerical value associated with the detected color is within a tolerance range (i.e., the numerical value associated with the requested color +/− the tolerance value), the detected color may be accepted. The automatic cleaning device may receive from the video camera the value of the detected color and/or the tolerance range.
In an embodiment, the automatic cleaning device may determine 610 whether to use any of the information received from the video camera in navigating its path. For example, the automatic cleaning device may receive 515 positional information from one or more sensors, such as sonar, radar and/or the like. In an embodiment, the automatic cleaning device may compare 620 the information that it receives from its sensors and the information that it receives from the video camera to information from a map of an area in which the automatic cleaning device is navigating.
In an embodiment, a map may be generated by the automatic cleaning device and/or another computing device during the automatic cleaning device's first navigation of the area. For example, the automatic cleaning device may be manually controlled through an area during which time the mobile robotic device may generate and store a map of the navigated area. In an embodiment, the mobile robotic device may compare 620 the information it receives 615 from its sensors and the information it receives from the video camera to the digital representation of the map to determine which information to use.
In an embodiment, the automatic cleaning device may use the information that has the least amount of error as compared to the automatic cleaning device's current position. For example, an automatic cleaning device may determine a current position using a map. It may compare the information received from its sensor and the information it receives from its video camera to determine which information has the least amount of error relative to its current position. The automatic cleaning device may adjust its position based on the information associated with the least amount of error.
In an embodiment, the automatic cleaning device may adjust 625 its position based on the most accurate information. The automatic cleaning device may use the information to adjust 625 its position, heading and/or the like. For example, an estimated position of the automatic cleaning device may be determined. The estimated position may include coordinates, a heading and/or the like. In an embodiment, an actual position may be determined based on the information associated with the detected area that is received by the automatic cleaning device. The estimated position may be compared to the actual position, and the automatic cleaning device may adjust 625 its position to compensate for any positional error that may exist. For example, the automatic cleaning device may navigate from its actual position to the estimated position.
In an embodiment, the automatic cleaning device may clean 630 at least a portion of its navigated path. For example, an automatic cleaning device may be able to determine one or more characteristics corresponding to its determined position. A characteristic may include, for example, a floor type, such as hard wood, tile, carpet and/or the like. A characteristic may include whether the position is in a high-traffic area, a low-traffic area and/or the like. In an embodiment, an automatic cleaning device may determine an appropriate cleaning method based on the determined characteristics. For example, the automatic cleaning device may vacuum a carpeted area, scrub and/or wax a hardwood or tile area and/or the like.
It will be appreciated that various of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications. Also that various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.
This application claims priority to and is a continuation of U.S. patent application Ser. No. 14/176,386, filed Feb. 10, 2014, which is a divisional application that claims priority to U.S. patent application Ser. No. 12/616,577, filed Nov. 11, 2009, now U.S. Pat. No. 8,679,260. The disclosures of each priority application are fully incorporated into this document. This application is also related to U.S. patent application Ser. No. 12/616,452, filed Nov. 11, 2009, now U.S. Pat. No. 8,423,225, the disclosure of which is fully incorporated by reference into this document.
Number | Date | Country | |
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Parent | 12616577 | Nov 2009 | US |
Child | 14176386 | US |
Number | Date | Country | |
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Parent | 14176386 | Feb 2014 | US |
Child | 15234836 | US |