Methods, systems, and apparatus, including computer programs encoded on computer storage media, for integrating sensor streams for robotic demonstration learning. One of the methods includes selecting, by a learning system for a robot, a base update rate for combining multiple sensor streams into a task state representation. The learning system repeatedly generates the task state representation at the base update rate, including combining, during each time period defined by the update rate, the task state representation from most recently updated sensor data processed by the plurality of neural networks. The learning system repeatedly uses the task state representations to generate commands for the robot at the base update rate.

The invention relates to a method for determining optimized program parameters for a robot program, wherein the robot program is used to control a robot having a manipulator, preferably in a robot cell, comprising the steps: creating the robot program by means of a component-based graphical programming system on the basis of user inputs, wherein the robot program is formed from program components which are parameterizable via program parameters, and wherein initial program parameters are generated for the program components of the robot program; providing an interface for selecting one or more critical program components, wherein optimizable program parameters can be defined for the critical program components; carrying out an exploration phase for exploring a parameter range in relation to the optimizable program parameters, the robot program being carried out multiple times, the parameter range being scanned for the critical program components and trajectories of the robot being recorded such that training data are present for the critical program components; carrying out a learning phase in order to generate component representatives for the critical program components of the robot program on the basis of the training data collected in the exploration phase, wherein a component representative represents a system model which, in the form of a differentiable function, maps a specified state of the robot and specified program parameters to a predicted trajectory; carrying out an inference phase for determining optimized program parameters for the critical program components of the robot program, wherein optimizable program parameters of the component representative are iteratively optimized in respect of a specified target function by means of a gradient-based optimization method using the component representative. The invention furthermore relates to a corresponding system.

Systems, devices, and methods for training and operating (semi-)autonomous robots to complete multiple different work objectives are described. A robot control system stores a library of reusable work primitives each corresponding to a respective basic sub-task or sub-action that the robot is operative to autonomously perform. A work objective is analyzed to determine a sequence (i.e., a combination and/or permutation) of reusable work primitives that, when executed by the robot, will complete the work objective. The robot executes the sequence of reusable work primitives to complete the work objective. The reusable work primitives may include one or more reusable grasp primitives that enable(s) a robot's end effector to grasp objects. Simulated instances of real physical robots may be trained in simulated environments to develop control instructions that, once uploaded to the real physical robots, enable such real physical robots to autonomously perform reusable work primitives.

Robotic systems, methods of operation of robotic systems, and storage media including processor-executable instructions are disclosed herein. The system may include a robot, at least one processor in communication with the robot, and an operator interface in communication with the robot and the at least one processor. The method may include executing a first set of autonomous robot control instructions which causes a robot to autonomously perform the at least one task in an autonomous mode, and generating a second set of autonomous robot control instructions from the first set of autonomous robot control instructions and a first set of environmental sensor data received from a senor. Execution of the second set of autonomous robot control instructions causes the robot to autonomously perform the at least one task. The method may include producing at least one signal that represents the second set of autonomous robot control instructions.

Robots, methods, and computer program products for training and operating (semi-) autonomous robots to complete multiple different work objectives are described. A robot accesses a library of reusable work primitives from a catalog of libraries of reusable work primitives, each reusable work primitive corresponding to a respective basic sub-task or sub-action that the robot is operative to autonomously perform. A work objective is analyzed to determine a sequence (i.e., a combination and/or permutation) of reusable work primitives that, when executed by the robot, will complete the work objective. The robot executes the sequence of reusable work primitives to complete the work objective. A robot can be deployed with an appropriate stored library (or access to an appropriate library) of reusable work primitives, based on what the robot is expected to do, or what service category or role the robot will operate in.

Robots, methods, and computer program products for training and operating (semi-) autonomous robots to complete multiple different work objectives are described. A robot accesses a library of reusable work primitives from a catalog of libraries of reusable work primitives, each reusable work primitive corresponding to a respective basic sub-task or sub-action that the robot is operative to autonomously perform. A work objective is analyzed to determine a sequence (i.e., a combination and/or permutation) of reusable work primitives that, when executed by the robot, will complete the work objective. The robot executes the sequence of reusable work primitives to complete the work objective. A robot can be deployed with an appropriate stored library (or access to an appropriate library) of reusable work primitives, based on what the robot is expected to do, or what service category or role the robot will operate in.

Robotic systems, methods of operation of robotic systems, and storage media including processor-executable instructions are disclosed herein. The system may include a robot, at least one processor in communication with the robot, and an operator interface in communication with the robot and the at least one processor. The method may include executing a first set of autonomous robot control instructions which causes a robot to autonomously perform the at least one task in an autonomous mode, and generating a second set of autonomous robot control instructions from the first set of autonomous robot control instructions and a first set of environmental sensor data received from a senor. Execution of the second set of autonomous robot control instructions causes the robot to autonomously perform the at least one task. The method may include producing at least one signal that represents the second set of autonomous robot control instructions.

An input control for providing motion commands to an actuator, including an input screen on which a plurality of movement symbols are arranged, each of which is associated with a motion command for the actuator, and which includes a sequence track for lining up copies of the movement symbols along an alignment direction, having a processor which is configured to interrogate the sequence track in order to determine a sequence of motion commands and to output the sequence of motion commands and/or an actuator control signal sequence which is dependent on the sequence of motion commands, and wherein. a sensor signal track is arranged in parallel with the sequence track, which is configured for displaying a sensor signal sequence of at least one sensor signal of a sensor system assigned to the actuator.

Systems, devices, and methods for training and operating (semi-)autonomous robots to complete multiple different work objectives are described. A robot control system stores a library of reusable work primitives each corresponding to a respective basic sub-task or sub-action that the robot is operative to autonomously perform. A work objective is analyzed to determine a sequence (i.e., a combination and/or permutation) of reusable work primitives that, when executed by the robot, will complete the work objective. The robot executes the sequence of reusable work primitives to complete the work objective. The reusable work primitives may include one or more reusable grasp primitives that enable(s) a robot's end effector to grasp objects. Simulated instances of real physical robots may be trained in simulated environments to develop control instructions that, once uploaded to the real physical robots, enable such real physical robots to autonomously perform reusable work primitives.

Systems, devices, and methods for training and operating (semi-)autonomous robots to complete multiple different work objectives are described. A robot control system stores a library of reusable work primitives each corresponding to a respective basic sub-task or sub-action that the robot is operative to autonomously perform. A work objective is analyzed to determine a sequence (i.e., a combination and/or permutation) of reusable work primitives that, when executed by the robot, will complete the work objective. The robot executes the sequence of reusable work primitives to complete the work objective. The reusable work primitives may include one or more reusable grasp primitives that enable(s) a robot's end effector to grasp objects. Simulated instances of real physical robots may be trained in simulated environments to develop control instructions that, once uploaded to the real physical robots, enable such real physical robots to autonomously perform reusable work primitives.