To provide a robot system equipped with an off-line programming device which can create a machining path consisting of a trajectory of any shape, and can reduce the workload required in teaching of the machining path of any shape. Provided is an off-line programming device which teaches a program of a robot equipped with a toll that machines a workpiece arranged within a work space, the off-line programming device including a trajectory information creation unit which creates trajectory information of any 3D shape consisting of at least one layer; and a trajectory information editing unit which edits line segments constituting the trajectory information of the any 3D shape consisting of at least one layer.

A robotic manipulator has a robotic controller that includes a programmable logic controller (PLC). The PLC can be configured to receive a planned motion path having a first path segment and an abort segment. The first path segment can be associated with a path to be followed by a joint of the robotic manipulator and is queued before the abort segment associated with the first path segment. The abort segment can be indicative of a path segment that in response to execution results in aborting an operation of the joint of the robotic manipulator. The PLC can be configured to validate the planned motion path based on an analysis of at least the first path segment and the abort segment. Further, upon successful validation of the planned motion path, the PLC can be configured to initiate execution of the first path segment by the joint of the robotic manipulator.

The invention relates to a robotic system with at least one robotic arm and a control unit, which is designed so that it can preset at least one predefined operation that can be carried out by the robotic system. In addition, the robotic system comprises at least one input device attached to the robotic arm which is designed so that the predefined operations of the robotic system can be parameterized by means of the input device. In this case, the input device is designed so that it can provide a user-directed feedback to a user of the robotic system when setting the execution of operations, the logical sequence of the operations and/or parameterizing the predefined operations for the robotic system.

The purpose is to enable an instructor who does not know any programming language to easily teach robot movements and operation content to a robot without using a teach pendant. This method for generating a robot operation program includes a step, using a GUI, for sequentially executing in a plurality of template element operation programs the feature of displaying a variable specification screen for specifying a variable of a certain template element operation program, and then storing the template element operation program for which the variable was specified in a storage unit as a custom element operation program. The plurality of template element operation programs is configured so that: one or more finger position coordinates specifying a robot motion required for the element operation corresponding to the program are included as variables; and the one or more finger position coordinates are all specified, thereby specifying the robot motion.

A system and method for machine understanding, using program induction, includes a visual cognitive computer including a set of components designed to execute predetermined primitive functions. The method includes determining programs using a program induction engine that interfaces with the visual cognitive computer to discover programs using the predetermined primitive functions and/or executes the discovered programs based on an input.

Embodiments of the present disclosure are directed to methods, computer program products, and computer systems of a robotic apparatus with robotic instructions replicating a food preparation recipe. In one embodiment, a robotic control platform, comprises one or more sensors; a mechanical robotic structure including one or more end effectors, and one or more robotic arms; an electronic library database of minimanipulations; a robotic planning module configured for real-time planning and adjustment based at least in part on the sensor data received from the one or more sensors in an electronic multi-stage process file, the electronic multi-stage process recipe file including a sequence of minimanipulations and associated timing data; a robotic interpreter module configured for reading the minimanipulation steps from the minimanipulation library and converting to a machine code; and a robotic execution module configured for executing the minimanipulation steps by the robotic platform to accomplish a functional result.

Embodiments of the present disclosure are directed to methods, computer program products, and computer systems of a robotic apparatus with robotic instructions replicating a food preparation recipe. In one embodiment, a robotic control platform, comprises one or more sensors; a mechanical robotic structure including one or more end effectors, and one or more robotic arms; an electronic library database of minimanipulations; a robotic planning module configured for real-time planning and adjustment based at least in part on the sensor data received from the one or more sensors in an electronic multi-stage process file, the electronic multi-stage process recipe file including a sequence of minimanipulations and associated timing data; a robotic interpreter module configured for reading the minimanipulation steps from the minimanipulation library and converting to a machine code; and a robotic execution module configured for executing the minimanipulation steps by the robotic platform to accomplish a functional result.

The present disclosure is directed to methods, computer program products, and computer systems for instructing a robot to prepare a food dish by replacing the human chef's movements and actions. Monitoring a human chef is carried out in an instrumented application-specific setting, a standardized robotic kitchen in this instance, and involves using sensors and computers to watch, monitor, record and interpret the motions and actions of the human chef, in order to develop a robot-executable set of commands robust to variations and changes in the environment, capable of allowing a robotic or automated system in a robotic kitchen to prepare the same dish to the standards and quality as the dish prepared by the human chef.

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.

A robotic controller is provided for generating sequences of movement primitives for sequential tasks of a robot having a manipulator. The controller includes at least one control processor, and a memory circuitry storing a dictionary including the movement primitives, a pretrained learning module, and a graph-search based planning module having instructions stored thereon. The controller to perform steps acquiring a planned task provided by an interface device operated by a user, wherein the planned task is represented by an initial state and a goal state with respect to an object, generating a planning graph by searching a feasible path of the object for the novel task using the graph-search based planning module and selecting movement primitives from the dictionary in the pretrained learning module, wherein the pretrained learning module has been trained based on demonstration tasks, parameterizing the feasible path represented by the movement primitives as dynamic movement primitives (DMPs) using the initial state and goal state, and implementing the parameterized feasible path as a trajectory according to the selected movement primitives using the manipulator of the robot by tracking and following the parameterized for the planned task.