Patents by Inventor Mario E. Munich
Mario E. Munich has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 10168709Abstract: A method of operating a mobile robot includes generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by a mobile robot responsive to navigation of the surface, identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern. Related methods, computing devices, and computer program products are also discussed.Type: GrantFiled: September 14, 2017Date of Patent: January 1, 2019Assignee: iRobot CorporationInventors: Alexander D. Kleiner, Mario E. Munich
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Publication number: 20180299275Abstract: A system and method for mapping parameter data acquired by a robot mapping system is disclosed. Parameter data characterizing the environment is collected while the robot localizes itself within the environment using landmarks. Parameter data is recorded in a plurality of local grids, i.e., sub-maps associated with the robot position and orientation when the data was collected. The robot is configured to generate new grids or reuse existing grids depending on the robot's current pose, the pose associated with other grids, and the uncertainty of these relative pose estimates. The pose estimates associated with the grids are updated over time as the robot refines its estimates of the locations of landmarks from which determines its pose in the environment. Occupancy maps or other global parameter maps may be generated by rendering local grids into a comprehensive map indicating the parameter data in a global reference frame extending the dimensions of the environment.Type: ApplicationFiled: March 14, 2018Publication date: October 18, 2018Inventors: Philip Fong, Ethan Eade, Mario E. Munich
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Publication number: 20180297208Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.Type: ApplicationFiled: April 10, 2018Publication date: October 18, 2018Inventors: Dhiraj Goel, Ethan Eade, Philip Fong, Mario E. Munich
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Publication number: 20180284792Abstract: A method of operating a mobile robot includes generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by a mobile robot responsive to navigation of the surface, identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern. Related methods, computing devices, and computer program products are also discussed.Type: ApplicationFiled: April 2, 2018Publication date: October 4, 2018Inventors: Alexander D. Kleiner, Mario E. Munich
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Patent number: 9969089Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.Type: GrantFiled: July 27, 2016Date of Patent: May 15, 2018Assignee: iRobot CorporationInventors: Dhiraj Goel, Ethan Eade, Philip Fong, Mario E. Munich
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Patent number: 9952053Abstract: A system and method for mapping parameter data acquired by a robot mapping system is disclosed. Parameter data characterizing the environment is collected while the robot localizes itself within the environment using landmarks. Parameter data is recorded in a plurality of local grids, i.e., sub-maps associated with the robot position and orientation when the data was collected. The robot is configured to generate new grids or reuse existing grids depending on the robot's current pose, the pose associated with other grids, and the uncertainty of these relative pose estimates. The pose estimates associated with the grids are updated over time as the robot refines its estimates of the locations of landmarks from which determines its pose in the environment. Occupancy maps or other global parameter maps may be generated by rendering local grids into a comprehensive map indicating the parameter data in a global reference frame extending the dimensions of the environment.Type: GrantFiled: August 1, 2016Date of Patent: April 24, 2018Assignee: iRobot CorporationInventors: Philip Fong, Ethan Eade, Mario E. Munich
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Publication number: 20180074508Abstract: A method of operating a mobile robot includes generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by a mobile robot responsive to navigation of the surface, identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern. Related methods, computing devices, and computer program products are also discussed.Type: ApplicationFiled: September 14, 2017Publication date: March 15, 2018Inventors: Alexander D. Kleiner, Mario E. Munich
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Patent number: 9910444Abstract: The invention is related to methods and apparatus that use a visual sensor and dead reckoning sensors to process Simultaneous Localization and Mapping (SLAM). These techniques can be used in robot navigation. Advantageously, such visual techniques can be used to autonomously generate and update a map. Unlike with laser rangefinders, the visual techniques are economically practical in a wide range of applications and can be used in relatively dynamic environments, such as environments in which people move. Certain embodiments contemplate improvements to the front-end processing in a SLAM-based system. Particularly, certain of these embodiments contemplate a novel landmark matching process. Certain of these embodiments also contemplate a novel landmark creation process. Certain embodiments contemplate improvements to the back-end processing in a SLAM-based system. Particularly, certain of these embodiments contemplate algorithms for modifying the SLAM graph in real-time to achieve a more efficient structure.Type: GrantFiled: February 3, 2016Date of Patent: March 6, 2018Assignee: iRobot CorporationInventors: Ethan Eade, Mario E. Munich, Philip Fong
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Publication number: 20170105592Abstract: A mobile robot system is provided that includes a docking station having at least two pose-defining fiducial markers. The pose-defining fiducial markers have a predetermined spatial relationship with respect to one another and/or to a reference point on the docking station such that a docking path to the base station can be determined from one or more observations of the at least two pose-defining fiducial markers. A mobile robot in the system includes a pose sensor assembly. A controller is located on the chassis and is configured to analyze an output signal from the pose sensor assembly. The controller is configured to determine a docking station pose, to locate the docking station pose on a map of a surface traversed by the mobile robot and to path plan a docking trajectory.Type: ApplicationFiled: December 23, 2016Publication date: April 20, 2017Inventors: Philip Fong, Jason Meltzer, Jens-Steffen Gutmann, Vazgen Karapetyan, Mario E. Munich
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Publication number: 20170052033Abstract: A system and method for mapping parameter data acquired by a robot mapping system is disclosed. Parameter data characterizing the environment is collected while the robot localizes itself within the environment using landmarks. Parameter data is recorded in a plurality of local grids, i.e., sub-maps associated with the robot position and orientation when the data was collected. The robot is configured to generate new grids or reuse existing grids depending on the robot's current pose, the pose associated with other grids, and the uncertainty of these relative pose estimates. The pose estimates associated with the grids are updated over time as the robot refines its estimates of the locations of landmarks from which determines its pose in the environment. Occupancy maps or other global parameter maps may be generated by rendering local grids into a comprehensive map indicating the parameter data in a global reference frame extending the dimensions of the environment.Type: ApplicationFiled: August 1, 2016Publication date: February 23, 2017Inventors: PHILIP FONG, Ethan Eade, Mario E. Munich
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Publication number: 20170031366Abstract: A proximity sensor includes first and second sensors disposed on a sensor body adjacent to one another. The first sensor is one of an emitter and a receiver. The second sensor is the other one of an emitter and a receiver. A third sensor is disposed adjacent the second sensor opposite the first sensor. The third sensor is an emitter if the first sensor is an emitter or a receiver if the first sensor is a receiver. Each sensor is positioned at an angle with respect to the other two sensors. Each sensor has a respective field of view. A first field of view intersects a second field of view defining a first volume that detects a floor surface within a first threshold distance. The second field of view intersects a third field of view defining a second volume that detects a floor surface within a second threshold distance.Type: ApplicationFiled: August 23, 2016Publication date: February 2, 2017Applicant: iRobot CorporationInventors: Steven V. Shamlian, Samuel Duffley, Nikolai Romanov, Dhiraj Goel, Frederic D. Hook, Mario E. Munich
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Patent number: 9538892Abstract: A mobile robot system is provided that includes a docking station having at least two pose-defining fiducial markers. The pose-defining fiducial markers have a predetermined spatial relationship with respect to one another and/or to a reference point on the docking station such that a docking path to the base station can be determined from one or more observations of the at least two pose-defining fiducial markers. A mobile robot in the system includes a pose sensor assembly. A controller is located on the chassis and is configured to analyze an output signal from the pose sensor assembly. The controller is configured to determine a docking station pose, to locate the docking station pose on a map of a surface traversed by the mobile robot and to path plan a docking trajectory.Type: GrantFiled: October 5, 2013Date of Patent: January 10, 2017Assignee: iRobot CorporationInventors: Philip Fong, Jason Meltzer, Steffen Gutmann, Vazgen Karapetyan, Mario E. Munich
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Patent number: 9534899Abstract: Vector Field SLAM is a method for localizing a mobile robot in an unknown environment from continuous signals such as WiFi or active beacons. Disclosed is a technique for localizing a robot in relatively large and/or disparate areas. This is achieved by using and managing more signal sources for covering the larger area. One feature analyzes the complexity of Vector Field SLAM with respect to area size and number of signals and then describe an approximation that decouples the localization map in order to keep memory and run-time requirements low. A tracking method for re-localizing the robot in the areas already mapped is also disclosed. This allows to resume the robot after is has been paused or kidnapped, such as picked up and moved by a user. Embodiments of the invention can comprise commercial low-cost products including robots for the autonomous cleaning of floors.Type: GrantFiled: November 9, 2012Date of Patent: January 3, 2017Assignee: iRobot CorporationInventors: Jens-Steffen Gutmann, Philip Fong, Mario E. Munich
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Publication number: 20160332304Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.Type: ApplicationFiled: July 27, 2016Publication date: November 17, 2016Inventors: Dhiraj Goel, Ethan Eade, Philip Fong, Mario E. Munich
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Patent number: 9442488Abstract: A proximity sensor includes first and second sensors disposed on a sensor body adjacent to one another. The first sensor is one of an emitter and a receiver. The second sensor is the other one of an emitter and a receiver. A third sensor is disposed adjacent the second sensor opposite the first sensor. The third sensor is an emitter if the first sensor is an emitter or a receiver if the first sensor is a receiver. Each sensor is positioned at an angle with respect to the other two sensors. Each sensor has a respective field of view. A first field of view intersects a second field of view defining a first volume that detects a floor surface within a first threshold distance. The second field of view intersects a third field of view defining a second volume that detects a floor surface within a second threshold distance.Type: GrantFiled: May 16, 2014Date of Patent: September 13, 2016Assignee: iRobot CorporationInventors: Steven V. Shamlian, Samuel Duffley, Nikolai Romanov, Dhiraj Goel, Frederic D. Hook, Mario E. Munich
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Patent number: 9427875Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.Type: GrantFiled: November 23, 2015Date of Patent: August 30, 2016Assignee: iRobot CorporationInventors: Dhiraj Goel, Ethan Eade, Philip Fong, Mario E. Munich
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Patent number: 9404756Abstract: A system and method for mapping parameter data acquired by a robot mapping system is disclosed. Parameter data characterizing the environment is collected while the robot localizes itself within the environment using landmarks. Parameter data is recorded in a plurality of local grids, i.e., sub-maps associated with the robot position and orientation when the data was collected. The robot is configured to generate new grids or reuse existing grids depending on the robot's current pose, the pose associated with other grids, and the uncertainty of these relative pose estimates. The pose estimates associated with the grids are updated over time as the robot refines its estimates of the locations of landmarks from which determines its pose in the environment. Occupancy maps or other global parameter maps may be generated by rendering local grids into a comprehensive map indicating the parameter data in a global reference frame extending the dimensions of the environment.Type: GrantFiled: November 17, 2015Date of Patent: August 2, 2016Assignee: iRobot CorporationInventors: Philip Fong, Ethan Eade, Mario E. Munich
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Publication number: 20160154408Abstract: The invention is related to methods and apparatus that use a visual sensor and dead reckoning sensors to process Simultaneous Localization and Mapping (SLAM). These techniques can be used in robot navigation. Advantageously, such visual techniques can be used to autonomously generate and update a map. Unlike with laser rangefinders, the visual techniques are economically practical in a wide range of applications and can be used in relatively dynamic environments, such as environments in which people move. Certain embodiments contemplate improvements to the front-end processing in a SLAM-based system. Particularly, certain of these embodiments contemplate a novel landmark matching process. Certain of these embodiments also contemplate a novel landmark creation process. Certain embodiments contemplate improvements to the back-end processing in a SLAM-based system. Particularly, certain of these embodiments contemplate algorithms for modifying the SLAM graph in real-time to achieve a more efficient structure.Type: ApplicationFiled: February 3, 2016Publication date: June 2, 2016Inventors: Ethan Eade, Mario E. Munich, Philip Fong
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Publication number: 20160143500Abstract: A mobile robot system is provided that includes a docking station having at least two pose-defining fiducial markers. The pose-defining fiducial markers have a predetermined spatial relationship with respect to one another and/or to a reference point on the docking station such that a docking path to the base station can be determined from one or more observations of the at least two pose-defining fiducial markers. A mobile robot in the system includes a pose sensor assembly. A controller is located on the chassis and is configured to analyze an output signal from the pose sensor assembly. The controller is configured to determine a docking station pose, to locate the docking station pose on a map of a surface traversed by the mobile robot and to path plan a docking trajectory.Type: ApplicationFiled: November 20, 2015Publication date: May 26, 2016Inventors: Philip Fong, Jason Meltzer, Jens-Steffen Gutmann, Vazgen Karapetyan, Mario E. Munich
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Publication number: 20160075032Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.Type: ApplicationFiled: November 23, 2015Publication date: March 17, 2016Inventors: Dhiraj Goel, Ethan Eade, Philip Fong, Mario E. Munich