Fanuc America Corporation

Fanuc Robotics America Corporation

Fanuc Corporation

Fanuc Robotics North America, Inc.

Min-Ren Jean

H Dean McGee

Jason Tsai

Sai-Kai Cheng

Chi-Keng Tsai

Hadi A Akeel

Hajime Suzuki

Kenneth W Krause

Eric C Lee

Shinichi Washizu

Rick E Wunderlich

Gordon Geheb

Leo Keselman

Derek Jung

Ganesh Kalbavi

Di Xiao

Bryan Thomas

Paul Skrna

William Lawson

Genesh Kalbavi

Gerald A Ross

Kyle Thornley

An augmented reality (AR) system for production-tuning of parameters for a visual tracking robotic picking system. The robotic picking system includes one or more robots configured to pick randomly-placed and randomly-oriented parts off a conveyor belt and place the parts in an available position, either on a second moving conveyor belt or on a stationary device such as a pallet. A visual tracking system identifies position and orientation of the parts on the feed conveyor. The AR system allows picking system tuning parameters including upstream, discard and downstream boundary locations to be visualized and controlled, real-time robot pick/place operations to be viewed with virtual boundaries, and system performance parameters such as part throughput rate and part allocation by robot to be viewed. The AR system also allows virtual parts to be used in simulations, either instead of or in addition to real parts.

Augmented reality visualization for robotic picking system

A method and apparatus for controlling a continuous machining process includes a robot, a machining tool, a table, and a raw parts supply mounted inside a machining cell enclosure. The table has first and second vises for holding parts. The machining tool is operated to machine a raw part in one of the vises while the robot is operated to pick a machined part from the other vise and then place another raw part into the other vise. The table can be fixed or rotatable. The robot places the picked machined parts on an exit conveyor to remove the machined parts from the enclosure.

Continuous machining with robotic table tracking of fixture

A robot controller capable of easily speeding up the motion of a robot by learning, without using a special device and teaching know-how. The robot controller has a storing part which stores a reference motion pattern of the robot; an inputting part which designates at least one of a working start region where a motion of the robot based on the reference motion pattern is initiated and a working end region where the motion of the robot is terminated; an automatic generating part which automatically generates a plurality of motion patterns of the robot based on the reference motion pattern and divided regions formed by dividing a working region at a predetermined resolution; and a learning control part which learns a motion speed-up ratio for speeding up the motion by changing a velocity or acceleration in relation to each of the automatically generated motion patterns.

Robot controller having function to simplify teaching operation and improve motion performance of robot

A system for picking and packing applications is provided. The system includes a plurality of robots and a plurality of robot controllers. Each robot controller includes a load re-balance subsystem, a load balance subsystem, a robot state change detector subsystem, a communicator subsystem, and a motion control subsystem. Each of the robot controllers is interconnected and in communication with one another via the communicator subsystems. Each of the robots has a workload that may be selectively balanced. A method for balancing the workloads of the robots using built-in processors which run motion control is also provided.

Method and apparatus for picking/packing applications

A method of controlling a robot () includes the steps of selecting an initial configuration from at least one of a first, second, and third sets to position a TCP at a starting point () along a path () and selecting a final configuration different than the initial configuration to position the TCP at an ending point (). Next, the TCP moves from the starting point () while maintaining the initial configuration, approaches the singularity between a first point () and a second point (), and selects one of the axes in response to reaching the first point (). The angle for the selected axis is interpolated from the first point () to the second point (). After the interpolation, the angles about the remaining axes are determined and positions the arms in the final configuration when the TCP reaches the second point () and moves to the ending point () while maintaining the final configuration.

Method of controlling a robot through a singularity

A robot calibration system includes a calibration sensor that provides an indication of when a first reference point that remains fixed relative to a robot base is a fixed distance from a second reference point that is located on the robot arm. The robot arm is moved through a plurality of orientations and each time that the fixed distance between the two reference points is achieved, robot joint position information is determined. The preferred calibration sensor includes a string that extends between the two reference points and activates a signal generator each time that the string is taut as caused by the orientation of the robot arm. The generated signal indicates that the two reference points are separated by the fixed distance. The determined robot joint positions are then used to determine a calibration factor which varies depending on the needs of a particular situation. Example calibration factors are useful for correcting errors in robot kinematic information, locating the workcell reference frame and locating the tool center point reference frame.

Robot calibration system

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Rochester Hills, MI, United States of America

Min-Ren Jean