Abstract: A method for automatically planning an optimal trajectory for a robot device includes obtaining a safety-related information comprising a safety zone having a safety condition for a movement behavior of the robot device that is supervised by a safety controller; obtaining a movement-related target parameter of the robot device that will be optimized for an operation of the robot device; and generating by a motion planner module the optimal trajectory for the robot device by incorporating the at least one safety-related information and the movement-related target parameter, wherein the generated optimal trajectory defines an optimal movement of the robot device that respects the safety condition and the movement-related target parameter.

Abstract: A method for defining a trajectory of a robot (1) for moving along a path from an initial point (A) to a final point (B) in a multidimensional space, each of whose points has a plurality of space coordinates, which are position and/or orientation coordinates, wherein the trajectory is a continuous map mapping an initial instant in time to the initial point (A), a final instant to the final point (B) and intermediate instants to intermediate points of the path, comprises the steps of defining (S3) a cost function which associates a cost value to a given trajectory, defining (S3) a pluridimensional subspace of said multidimensional space and determining (S4) among trajectories extending along different paths of said subspace, a trajectory which minimizes the cost function.

Abstract: A method for determining and calibrating a 3D representation of a robot cell includes a) obtaining cell data that includes environment data from a mobile sensor, wherein the environment data comprises a set of images of the robot cell from a first viewpoint; b) determining a 3D representation of the robot cell using the cell data; c) calibrating the 3D representation using a known geometry of the industrial robot; d) visualizing the 3D representation at the calibrated location and orientation in the robot cell in simulation software; e) determining the quality of the 3D representation; and f) repeating steps a)-e) when the quality of the 3D representation is smaller than a predetermined threshold.

Abstract: A method for applying machine learning to an application includes: a) generating a candidate policy by a learner; b) executing a program in at least one simulated application based on a set of candidate parameters provided based on the candidate policy and a state of the at least one simulated application, execution of the program providing interim results of tested sets of candidate parameters based on a measured performance information of the execution of the program; c) collecting a predetermined number of interim results and providing an end result based on a combination of the candidate parameters and/or the state with the measured performances information by a trainer; and d) generating a new candidate policy by the learner based on the end result.

Abstract: A method for automatically setting up a safety function configuration for a robot device includes obtaining a distance information between at least one moving part of the robot device and a defined position point in an environment of the robot device; comparing the distance information with a minimum gap criterion that defines a minimum distance between the at least one moving part of the robot device and the defined position point in the environment of the robot device, determining automatically a corresponding safety function configuration for the robot device in a dedicated workspace area depending on a deviation of the distance information and the minimum gap criterion.

Abstract: A method for optimizing a geometric path for a robot device around an obstacle includes providing the geometric path having a target position point at an intersection of first and second segments; defining a blending zone around the target position point, wherein the blending zone is a curve blending the first segment into the second segment; and optimizing the size of the blending zone by shifting the start point along the first segment and the end point along the second segment to find an optimal blending zone of the at least first blending zone that corresponds to a best cost function according to a defined criterion between the curve start point of the first segment and the curve end point of the second segment on the geometric path, wherein the optimal blending zone of the at least first blending zone satisfies at least one predefined condition.

Abstract: A method includes generating a first trajectory based on a query parameter using a conventional motion planner that plans a geometric path in a first step and optimizes an evolution in a second step to generate the first trajectory; generating a second trajectory using a learning-based motion planner; applying a post process to validate an optimized second trajectory based on the second trajectory; comparing the first trajectory with the optimized second trajectory and selecting the trajectory that meets the at least one performance criterion; and performing a background process improving the learning-based motion planner by feeding an optimal motion planner that integrates path and trajectory generation with the at least one query parameter to generate training data; and training the first learning-based motion planner using the training data, wherein at least one parameter of the first learning-based motion planner is input for the second learning-based motion planner.

Abstract: A method for identifying hazards in a robot application comprises a) providing a model of an application environment of a robot, the application environment extending beyond the limits of a movement range of the robot, the movement range comprising all points that the robot can occupy in any pose it is capable of assuming; b) identifying at least one point in the environment suitable for supporting a person; c) for each point identified in step b), defining a safety space above the point, the safety space comprising a volume expected to be occupied by a person supported by the point and a safety range around the volume; d) identifying one of the at least one point identified in step b) as hazardous when the safety space associated to said point overlaps with the movement range of the robot.

Abstract: A robot application development system and method includes a robot application unit that determines a robot application, which defines the industrial robot in a robot workspace. An input interface receives robot application information. An object data interface receives work piece information. A gripper finger design unit determines a gripper finger design. The robot application unit determines the robot application using the robot application information. The gripper finger design unit determines the gripper finger design using the work piece information and the robot application information.

Abstract: A method for implementing a safety configuration for a manipulator comprising an end effector comprises: a) reading an action instruction from a manipulator control program, the instruction defining at least one of a path to be followed by the end effector, a target position to be reached by the end effector, a target pose to be assumed by the end effector and an action to be carried out by a tool wielded by the end effector; b) reading at least one constraint instruction from the manipulator control program, the constraint instruction defining a constraint to be observed while carrying out an action instruction; and c) carrying out the action instruction read in step a) while respecting the constraint defined in the at least one constraint instruction, or transferring the manipulator into a safety mode if violation of the at least one constraint is detected while carrying out the action instruction.

Abstract: A method of responsive robot path planning implemented in a robot controller, including: providing a plurality of potential motion paths of a robot manipulator, wherein the potential motion paths are functionally equivalent with regard to at least one initial or final condition, a transportation task and/or a workpiece processing task; causing an operator interface to visualize the potential motion paths, wherein the operator interface is associated with an operator sharing a workspace with the robot manipulator; obtaining operator behavior during the visualization; and selecting at least one preferred motion path based on the operator behavior. A method in an operator interface, including obtaining from a robot controller a plurality of potential motion paths of the robot manipulator; visualizing the potential motion paths; sensing operator behavior during the visualization; and making the operator behavior available to the robot controller.

Abstract: A method of handling safety of an industrial robot in a workspace, the method including providing a geometric region by a monitoring system, where the geometric region is defined in relation to the industrial robot and/or in relation to the workspace, and where the geometric region is associated with at least one condition for being fulfilled by the industrial robot; communicating the geometric region from the monitoring system to a robot control system of the industrial robot; determining a movement of the industrial robot by the robot control system based on the geometric region and the at least one condition; executing the movement by the industrial robot; and monitoring, by the monitoring system, the execution of the movement with respect to the geometric region and the at least one condition.

Abstract: A method for trajectory planning in a robotic system comprising at least two robotic units includes a state vector of each robotic unit, which comprises position components and velocity components and is variable with time and independently from input into every other robotic unit. A trajectory defines the motion of said robotic units from an initial state to a final state and is determined by finding the trajectory that minimizes a predetermined cost function. The cost function is set to be a function of the state vectors of all robotic units, and is minimized under a constraint which defines a vector difference between at least the position components of the state vectors of said robotic units at an instant of said trajectory.

Abstract: A method for controlling displacement of a robot from an initial pose to a target pose includes providing a movement command, which specifies at least the target pose and an nominal path to be followed from the initial pose to the target pose; associating with the command an allowed deviation from the nominal path; identifying a real path that deviates from the nominal path by no more than the allowed deviation; and controlling the robot to move along said real path.

Abstract: A method of programming an industrial robot includes: providing the robot, the robot having a robot arm with an end-effector mounted thereto which is controlled by a robot control unit to manipulate a workpiece which is arranged in a workplace of the robot; associating a target coordinate system with the workplace; taking an image of the workplace and the workpiece by an image capturing device; transmitting the image to a computing device having a human-machine-interface to generate control code for controlling the robot, which is transmitted to the robot control unit; capturing an image of the workplace and the workpiece to be manipulated by the robot; transferring the captured image to the computing device and displaying the captured image on a display associated with the computing device; and displaying the workpiece on the display; marking the workpiece with a marker-object on the display.

Abstract: A robot system includes a robot, the robot including a base and an end effector that is movable relative to the base; and a processing target, the processing target being approachable by the end effector along at least one preferred direction; wherein the processing target is mounted movably relative to the base at least temporarily and at least in the preferred direction.

Abstract: A system and method for testing the padding of a robotic manipulator includes at least one sensor; a processing unit; and an output unit. The at least one sensor is configured to acquire sensor data of a robotic manipulator. The at least one sensor is configured to provide the sensor data to the processing unit. The processing unit is configured to determine information relating to padding applied to the robotic manipulator, wherein the determination comprises a comparison of the sensor data with reference data. The output unit is configured to output the information relating to the padding applied to the robotic manipulator.

Abstract: A robot application development system and method includes a robot application unit that determines a robot application, which defines the industrial robot in a robot workspace. An input interface receives robot application information. An object data interface receives work piece information. A gripper finger design unit determines a gripper finger design. The robot application unit determines the robot application using the robot application information. The gripper finger design unit determines the gripper finger design using the work piece information and the robot application information.

Abstract: A method for estimating a wrench acting on a reference point of a robot includes the steps of: a) measuring at least one component, but not all components, of the wrench; and b) estimating non-measured components of the wrench based on a dynamical model of the robot while taking into account the measured components.

Abstract: A method for applying machine learning to an application includes: a) generating a set of candidate parameters by a learner; b) executing a program in at least one simulated application based on the set of candidate parameters and providing interim results of tested sets of candidate parameters based on a measured performance information of the execution of the program; c) collecting a predetermined number of interim results and providing an end result based on a combination of the candidate parameters and the measured performance information by a trainer; and d) generating a new set of candidate parameters by the learner based on the end result for execution by the unchanged program.