In one aspect, a method for controlling a compliant-controlled robot includes performing a boundary monitoring of the robot and controlling movement of the robot with a return force that is predetermined by control technology. If the robot is already in a blocked area upon activation of the boundary monitoring, then a first return force operates to return the robot from a current position in the blocked area toward a boundary of the blocked area. If the robot arrived at the current position in the blocked area after activation of the boundary monitoring, then a second return force operates to return the robot from the current position toward the boundary. The first return force is at least temporarily less than the second return force.

The systems and methods provide an action recognition and analytics tool for use in manufacturing, health care services, shipping, retailing and other similar contexts. Machine learning action recognition can be utilized to determine cycles, processes, actions, sequences, objects and or the like in one or more sensor streams. The sensor streams can include, but are not limited to, one or more video sensor frames, thermal sensor frames, infrared sensor frames, and or three-dimensional depth frames. The analytics tool can provide for analyzing ergonomic data from the one or more sensor streams.

A computing system identifies a trajectory example generated by a human operator. The trajectory example includes trajectory information of the human operator while performing a task to be learned by a control system of the computing system. Based on the trajectory example, the computing system trains the control system to perform the task exemplified in the trajectory example. Training the control system includes generating an output trajectory of a robot performing the task. The computing system identifies an updated trajectory example generated by the human operator based on the trajectory example and the output trajectory of the robot performing the task. Based on the updated trajectory example, the computing system continues to train the control system to perform the task exemplified in the updated trajectory example.

A computing system identifies a trajectory example generated by a human operator. The trajectory example includes trajectory information of the human operator while performing a task to be learned by a control system of the computing system. Based on the trajectory example, the computing system trains the control system to perform the task exemplified in the trajectory example. Training the control system includes generating an output trajectory of a robot performing the task. The computing system identifies an updated trajectory example generated by the human operator based on the trajectory example and the output trajectory of the robot performing the task. Based on the updated trajectory example, the computing system continues to train the control system to perform the task exemplified in the updated trajectory example.

Provided is a technique that allows even a person without knowledge on robots to intuitively and efficiently teach a work motion a robot by a work demonstration while maintaining a normal human motion as much as possible, and that can reduce the man-hours for pre-adjustment of teaching, facilitate the introduction, etc. A robot teaching method is a method for performing teaching for generating a motion of a robotic hand mechanism corresponding to a work motion including an operation on an operation object by a hand of a teacher based on measurement of a work motion, and includes, as steps performed by a computer system: a step of acquiring a first measured pose obtained by measuring a pose of the operation object and a second measured pose obtained by measuring a pose of the hand of the teacher during the work motion; a step of detecting the operation on the operation object by the teacher; and a step of generating a teaching pose for generating the robotic motion data based on the first measured pose, the second measured pose, and the detected operation.

Provided is a technique that allows even a person without knowledge on robots to intuitively and efficiently teach a work motion a robot by a work demonstration while maintaining a normal human motion as much as possible, and that can reduce the man-hours for pre-adjustment of teaching, facilitate the introduction, etc. A robot teaching method is a method for performing teaching for generating a motion of a robotic hand mechanism corresponding to a work motion including an operation on an operation object by a hand of a teacher based on measurement of a work motion, and includes, as steps performed by a computer system: a step of acquiring a first measured pose obtained by measuring a pose of the operation object and a second measured pose obtained by measuring a pose of the hand of the teacher during the work motion; a step of detecting the operation on the operation object by the teacher; and a step of generating a teaching pose for generating the robotic motion data based on the first measured pose, the second measured pose, and the detected operation.

A method for training and/or testing a robot control module. The method includes generating an instruction specified by a robot control module configured for robot training and/or testing, the instruction indicating how a human-driven robot task is to be performed when training and/or testing the robot control module; providing the instruction to a mixed reality device worn by a human data collector, the mixed device rendering the instruction in a manner that shows the human data collector how to perform the human-driven robot task; collecting performance data and environmental data in response to the human data collector attempting to perform the human-driven robot task using the data collection device; receiving feedback data in response to the human data collector attempting to perform the human-driven robot task specified by the instruction; and updating the robot control module using the feedback data and the collected performance and environmental data.

The invention relates to a robot controller controlling a robot arm, the robot controller is configured to maintain the robot arm in a static posture when only gravity is acting on the robot arm and allow change in posture of the robot arm when an external force different from gravity is applied to the robot arm. The free-drive mode of operation is activatable by a user establishing a free-drive activation signal to the robot controller, which then is configured to initiate a free-drive mode activation sequence including the steps of: in a predetermined activation sequence period of time monitor a value of at least one joint sensor parameter, and compare this value to a free-drive activation joint sensor parameter threshold value. The robot controller is configured to switch to the free-drive mode of operation if the at least one value does not exceed the free-drive activation joint sensor parameter threshold value within the predetermined activation sequence period of time.

The invention relates to a robot controller controlling a robot arm, the robot controller is configured to maintain the robot arm in a static posture when only gravity is acting on the robot arm and allow change in posture of the robot arm when an external force different from gravity is applied to the robot arm. The free-drive mode of operation is activatable by a user establishing a free-drive activation signal to the robot controller, which then is configured to initiate a free-drive mode activation sequence including the steps of: in a predetermined activation sequence period of time monitor a value of at least one joint sensor parameter, and compare this value to a free-drive activation joint sensor parameter threshold value. The robot controller is configured to switch to the free-drive mode of operation if the at least one value does not exceed the free-drive activation joint sensor parameter threshold value within the predetermined activation sequence period of time.

The invention relates to a robot controller controlling a robot arm, the robot controller is configured to maintain the robot arm in a static posture when only gravity is acting on the robot arm and allow change in posture of the robot arm when an external force different from gravity is applied to the robot arm. The free-drive mode of operation is activatable by a user establishing a free-drive activation signal to the robot controller, which then is configured to:monitor a value of at least one joint sensor parameter;compare the value of the mode of joint sensor parameter to a maintain free-drive joint sensor parameter threshold value;maintain the robot arm in said free-drive mode of operation for a predetermined maintain free-drive period of time; andleave the free-drive mode of operation if the value of the joint sensor parameter does not exceed the maintain free-drive joint sensor parameter threshold value within the maintain free-drive period of time.