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Mario Enrique Munich

from La Canada, CA
Age ~58
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Also known as:
Mario E Munich, Mario Te Munich, Mario E Gainza, Mario Muich
Phone and address:
5653 Bramblewood Rd, La Canada, CA 91011
(626) 818-6614
Related to:
Mirena Munich, 25Maria E Gainza, 54Pedro MunichPablo R MunichHaydee GainzaMaria E Gainza, 55
Connected to:
Matthew A Munich, 52Richard L Munich, 86William F Munich, 80Marc W Munichman, 41Angel I Municio, 53Lauren M Munick, 35Grace E Munie, 70Ronda M Munie, 67Susan G Munie, 54Aletia Munien, 41

Mario Munich Phones & Addresses

  • 5653 Bramblewood Rd, La Canada Flt, CA 91011 (626) 818-6614
  • La Canada, CA
  • 440 Ramona Ave, Sierra Madre, CA 91024 (626) 355-5718
  • Arcadia, CA
  • Monrovia, CA
  • Wilmington, DE
  • San Francisco, CA
  • Pasadena, CA
  • Los Angeles, CA

Resumes

Resumes

Mario Munich Photo 1

Vp Of Research And Development At Evolution Robotics

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Location:
Greater Los Angeles Area
Industry:
Computer Software
Mario Munich Photo 2

Mario Munich

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Business Records

Name / Title
Company / Classification
Phones & Addresses
Mario Munich
President
INTELLIGENT ROBOTICS CONSULTING, INC
Business Consulting Services
5653 Bramblewood Rd, La Canada Flintridge, CA 91011
639 E Grandview Ave, Sierra Madre, CA 91024

Publications

Us Patents

Camera-Based Handwriting Tracking

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US Patent:
6633671, Oct 14, 2003
Filed:
Jan 28, 1999
Appl. No.:
09/239920
Inventors:
Mario E. Munich - Pasadena CA
Pietro Perona - Altadena CA
Assignee:
California Institute of Technology - Pasadena CA
International Classification:
G06K 900
US Classification:
382187, 215123, 215174
Abstract:
A system for processing handwriting that uses an ordinary camera as an image input device. The output of a single camera is used to produce a probability function that indicates the likelihood of whether the pen is touching the paper. The function uses clues including ink on the page and/or shadows. Another embodiment uses both pen up and pen down information to dynamically time warp-fit the information to fit it to a template.

Systems And Methods For Merchandise Automatic Checkout

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US Patent:
7337960, Mar 4, 2008
Filed:
Feb 28, 2005
Appl. No.:
10/554516
Inventors:
Jim Ostrowski - South Pasadena CA, US
Mario Munich - Sierra Madre CA, US
John Wiseman - Los Angeles CA, US
Assignee:
Evolution Robotics, Inc. - Pasadena CA
International Classification:
G06K 15/00
US Classification:
235383
Abstract:
Systems and methods for automatically checking out items located on a moving conveyor belt for the purpose of increasing the efficiency of a checkout process and revenue at a point-of-sale. The system includes a conveyor subsystem for moving the items, a housing that enclosed a portion of the conveyor subsystem, a lighting subsystem that illuminates an area within the housing, visual sensors that can take images of the items including UPCs, and a checkout system that receives the images from the visual sensors and automatically identifies the items. The system may include a scale subsystem located under the conveyor subsystem to measure the weights of the items, where the weight of each item is used to check if the corresponding item is identified correctly. The system relies on matching visual features from images stored in a database to match against features extracted from images taken by the visual sensors.

Systems And Methods For Merchandise Automatic Checkout

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US Patent:
8430311, Apr 30, 2013
Filed:
Feb 29, 2008
Appl. No.:
12/074263
Inventors:
Jim Ostrowski - South Pasadena CA, US
Mario Munich - Sierra Madre CA, US
John Wiseman - Los Angeles CA, US
Assignee:
Datalogic ADC, Inc. - Eugene OR
International Classification:
G06K 15/00
US Classification:
235383
Abstract:
Systems and methods for automatically checking out items located on a moving conveyor belt for the purpose of increasing the efficiency of a checkout process and revenue at a point-of-sale. The system includes a conveyor subsystem for moving the items, a housing that enclosed a portion of the conveyor subsystem, a lighting subsystem that illuminates an area within the housing, visual sensors that can take images of the items including UPCs, and a checkout system that receives the images from the visual sensors and automatically identifies the items. The system may include a scale subsystem located under the conveyor subsystem to measure the weights of the items, where the weight of each item is used to check if the corresponding item is identified correctly. The system relies on matching visual features from images stored in a database to match against features extracted from images taken by the visual sensors.

Localization By Learning Of Wave-Signal Distributions

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US Patent:
20110125323, May 26, 2011
Filed:
Nov 5, 2010
Appl. No.:
12/940937
Inventors:
Steffen Gutmann - Pasadena CA, US
Ethan Eade - Pasadena CA, US
Philip Fong - Pasadena CA, US
Mario Munich - Sierra Madre CA, US
Assignee:
EVOLUTION ROBOTICS, INC. - Pasadena CA
International Classification:
G05B 19/00
G06F 15/00
G06F 19/00
US Classification:
700258, 702150, 702 94
Abstract:
A robot having a signal sensor configured to measure a signal, a motion sensor configured to measure a relative change in pose, a local correlation component configured to correlate the signal with the position and/or orientation of the robot in a local region including the robot's current position, and a localization component configured to apply a filter to estimate the position and optionally the orientation of the robot based at least on a location reported by the motion sensor, a signal detected by the signal sensor, and the signal predicted by the local correlation component. The local correlation component and/or the localization component may take into account rotational variability of the signal sensor and other parameters related to time and pose dependent variability in how the signal and motion sensor perform. Each estimated pose may be used to formulate new or updated navigational or operational instructions for the robot.

Systems And Methods For Vslam Optimization

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US Patent:
20120121161, May 17, 2012
Filed:
Sep 23, 2011
Appl. No.:
13/244221
Inventors:
Ethan Eade - Seattle WA, US
Mario E. Munich - Sierra Madre CA, US
Philip Fong - Pasadena CA, US
Assignee:
EVOLUTION ROBOTICS, INC. - Pasadena CA
International Classification:
G06K 9/00
US Classification:
382153, 901 1
Abstract:
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.

Management Of Resources For Slam In Large Environments

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US Patent:
20130138246, May 30, 2013
Filed:
Nov 9, 2012
Appl. No.:
13/673926
Inventors:
Jens-Steffen Gutmann - Pasadena CA, US
Dhiraj Goel - Pasadena CA, US
Mario E. Munich - Sierra Madre CA, US
International Classification:
G05D 1/02
US Classification:
700253, 901 1, 901 47
Abstract:
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.

Re-Localization Of A Robot For Slam

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US Patent:
20130138247, May 30, 2013
Filed:
Nov 9, 2012
Appl. No.:
13/673928
Inventors:
Jens-Steffen Gutmann - Pasadena CA, US
Philip Fong - Los Angeles CA, US
Mario E. Munich - Sierra Madre CA, US
International Classification:
G05D 1/02
US Classification:
700253, 901 1, 901 47
Abstract:
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.

Carpet Drift Estimation Using Differential Sensors Or Visual Measurements

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US Patent:
20130331988, Dec 12, 2013
Filed:
Jun 7, 2013
Appl. No.:
13/913258
Inventors:
Ethan Eade - Seattle WA, US
Philip Fong - Los Angeles CA, US
Mario E. Munich - Sierra Madre CA, US
International Classification:
G05D 1/02
US Classification:
700254
Abstract:
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.
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Mario Enrique Munich from La Canada, CA, age ~58 Get Report