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公开(公告)号：US20180180421A1
公开(公告)日：2018-06-28
申请号：US15390460
申请日：2016-12-23
Applicant: X Development LLC
Inventor： Dirk Holz
CPC classification number: G01C21/206 , G01C21/005 , G01S17/88 , G05D1/024 , G05D1/0272 , G05D1/0274 , G05D2201/0216
Abstract: An example method includes determining locations of a plurality of candidate landmarks in relation to a robot based on sensor data from at least one sensor on the robot. The method further includes determining a plurality of sample sets, wherein each sample set comprises a subset of the plurality of candidate landmarks and a plurality of corresponding mapped landmarks. The method also includes determining a transformation for each sample set that relates the candidate landmarks from the subset to the corresponding mapped landmarks. The method additionally includes applying the determined transformation for each sample set to the plurality of candidate landmarks to determine a number of inliers associated with each sample set based on distances between the transformed plurality of candidate landmarks and a plurality of neighbouring mapped landmarks. The method further includes selecting a sample set from the plurality based on the number of inliers associated with each sample set. The method still further includes estimating a pose of the robot based on the selected sample set.
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公开(公告)号：US20210011482A1
公开(公告)日：2021-01-14
申请号：US17034795
申请日：2020-09-28
Applicant: X Development LLC
Inventor： Dirk Holz , Elizabeth Murphy
Abstract: One method disclosed includes identifying, in a map of markers fixed in an environment, two co-located markers within a threshold distance of each other, where each of the two co-located markers has a non-overlapping visibility region. The method further includes determining a set of detected markers based on sensor data from a robotic device. The method additionally includes identifying, from the set of detected markers, a detected marker proximate to a first marker of the two co-located markers. The method also includes enforcing a visibility constraint based on the non-overlapping visibility region of each of the two co-located markers to determine an association between the detected marker and a second marker of the two co-located markers. The method further includes determining a location of the robotic device in the environment relative to the map based on the determined association.
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公开(公告)号：US10852740B2
公开(公告)日：2020-12-01
申请号：US16147082
申请日：2018-09-28
Applicant: X Development LLC
Inventor： Elizabeth Murphy , Dirk Holz
Abstract: One method disclosed includes determining a map of markers fixed in an environment, where the map of markers includes a location and an orientation of each marker. The method further includes determining locations of a set of detected markers relative to the map based on a location of a robotic device relative to the map and based on sensor data from the robotic device. The method also includes associating a detected marker from the set of detected markers with a mapped marker based on the determined location of the detected marker relative to the map and based on a visibility constraint related to the orientation of the mapped marker. The method additionally includes adjusting, in the map, the orientation of the mapped marker based on the determined location of the detected marker relative to the map.
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公开(公告)号：US20200242396A1
公开(公告)日：2020-07-30
申请号：US16845544
申请日：2020-04-10
Applicant: X Development LLC
Inventor： Dirk Holz , Troy Straszheim
Abstract: Examples relate to simultaneous localization and calibration. An example implementation may involve receiving sensor data indicative of markers detected by a sensor on a vehicle located at vehicle poses within an environment, and determining a pose graph representing the vehicle poses and the markers. For instance, the pose graph may include edges associated with a cost function representing a distance measurement between matching marker detections at different vehicle poses. The distance measurement may incorporate the different vehicle poses and a sensor pose on the vehicle. The implementation may further involve determining a sensor pose transform representing the sensor pose on the vehicle that optimizes the cost function associated with the edges in the pose graph, and providing the sensor pose transform. In further examples, motion model parameters of the vehicle may be optimized as part of a graph-based system as well or instead of sensor calibration.
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Patent Agency Ranking
公开(公告)号：US10697779B2
公开(公告)日：2020-06-30
申请号：US15494216
申请日：2017-04-21
Applicant: X Development LLC
Inventor： Dirk Holz
IPC: G01C21/26 , G01C21/28 , G01S5/16 , G05D1/02 , G01S17/87 , G01S7/48 , G05D1/00 , G01S17/04 , G01C21/20
Abstract: Embodiments are provided that include receiving sensor data from a sensor positioned at a plurality of positions in an environment. The environment includes a plurality of landmarks. The embodiments also include determining, based on the sensor data, a subset of the plurality of landmarks detected at each of the plurality of positions. The embodiments further include determining, based on the subset of the plurality of landmarks detected at each of the plurality of positions, a detection frequency of each landmark. The embodiments additionally include determining, based on the determined detection frequency of each landmark, a localization viability metric associated with each landmark. The embodiments still further include providing for display, via a user interface, a map of the environment. The map includes an indication of the localization viability metric associated with each landmark.
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公开(公告)号：US10650270B2
公开(公告)日：2020-05-12
申请号：US15727726
申请日：2017-10-09
Applicant: X Development LLC
Inventor： Dirk Holz , Troy Straszheim
Abstract: Examples relate to simultaneous localization and calibration. An example implementation may involve receiving sensor data indicative of markers detected by a sensor on a vehicle located at vehicle poses within an environment, and determining a pose graph representing the vehicle poses and the markers. For instance, the pose graph may include edges associated with a cost function representing a distance measurement between matching marker detections at different vehicle poses. The distance measurement may incorporate the different vehicle poses and a sensor pose on the vehicle. The implementation may further involve determining a sensor pose transform representing the sensor pose on the vehicle that optimizes the cost function associated with the edges in the pose graph, and providing the sensor pose transform. In further examples, motion model parameters of the vehicle may be optimized as part of a graph-based system as well or instead of sensor calibration.
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公开(公告)号：US10328578B2
公开(公告)日：2019-06-25
申请号：US15494227
申请日：2017-04-21
Applicant: X Development LLC
Inventor： Dirk Holz
IPC: G06K9/00 , B25J9/16 , G05B19/402 , B66F9/06 , B66F9/00 , B66F9/075 , G06T7/73 , G06T7/13 , G05D1/02
Abstract: Example implementations may relate methods and systems for detecting, recognizing, and localizing pallets. For instance, a computing system may receive sensor data representing aspects of an environment, and identify a set of edge points in the sensor data. The computing system may further determine a set of line segments from the set of edge points where each line segment may fit to a subset of the set of edge points. Additionally, the computing system may also filter the set of line segments to exclude line segments that have a length outside a height range and a width range associated with dimensions of a pallet template, and identify, from the filtered set of line segments, a subset of line segments that align with the pallet template. Based on the identified subset of line segments, the computing system may determine a pose of a pallet in the environment.
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公开(公告)号：US20180307941A1
公开(公告)日：2018-10-25
申请号：US15727726
申请日：2017-10-09
Applicant: X Development LLC
Inventor： Dirk Holz , Troy Straszheim
CPC classification number: G06K9/6214 , B66F9/00 , B66F9/0755 , G01C21/20 , G01C21/206 , G05D1/024 , G05D1/0244 , G05D1/0274 , G05D2201/0216 , G06T2207/30244 , G06T2207/30248 , G06T2207/30252
Abstract: Examples relate to simultaneous localization and calibration. An example implementation may involve receiving sensor data indicative of markers detected by a sensor on a vehicle located at vehicle poses within an environment, and determining a pose graph representing the vehicle poses and the markers. For instance, the pose graph may include edges associated with a cost function representing a distance measurement between matching marker detections at different vehicle poses. The distance measurement may incorporate the different vehicle poses and a sensor pose on the vehicle. The implementation may further involve determining a sensor pose transform representing the sensor pose on the vehicle that optimizes the cost function associated with the edges in the pose graph, and providing the sensor pose transform. In further examples, motion model parameters of the vehicle may be optimized as part of a graph-based system as well or instead of sensor calibration.
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公开(公告)号：US20180304468A1
公开(公告)日：2018-10-25
申请号：US15494227
申请日：2017-04-21
Applicant: X Development LLC
Inventor： Dirk Holz
IPC: B25J9/16 , G05B19/402 , B66F9/06
CPC classification number: B25J9/1697 , B66F9/00 , B66F9/063 , B66F9/0755 , G05B19/402 , G05B2219/37582 , G05D1/0225 , G05D1/0248 , G05D2201/0216 , G06T7/13 , G06T7/75 , G06T2207/10028 , G06T2207/30244 , G06T2207/30252
Abstract: Example implementations may relate methods and systems for detecting, recognizing, and localizing pallets. For instance, a computing system may receive sensor data representing aspects of an environment, and identify a set of edge points in the sensor data. The computing system may further determine a set of line segments from the set of edge points where each line segment may fit to a subset of the set of edge points. Additionally, the computing system may also filter the set of line segments to exclude line segments that have a length outside a height range and a width range associated with dimensions of a pallet template, and identify, from the filtered set of line segments, a subset of line segments that align with the pallet template. Based on the identified subset of line segments, the computing system may determine a pose of a pallet in the environment.
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