A human-collaborative robot system includes a first force detection section that detects external force acting on a robot; a second force detection section that detects only an operating force acting on the robot when a human manually operates the robot; and a safety assurance operation command section that, in the case where the external force detected by the first force detection section exceeds a predetermined threshold value, commands a safety assurance operation of causing the robot to move in a direction that reduces the external force or causing the robot to stop. When the human is manually operating the robot while the robot is in the stopped state, the safety assurance operation command section compares a value obtained by subtracting the operating force detected by the second force detection section from the external force detected by the first force detection section with a predetermined threshold value.

A method for controlling a human-robot collaboration (HRC) system wherein the HRC system includes at least one manipulator having an end effector. The method includes using the end effector in a first operating mode, wherein the end effector is operated with reduced power; monitoring whether a desired object is manipulated when the end effector is used in the first operating mode; and increasing the power used to operate the end effector in order to use the end effector in a second operating mode when the monitoring indicates that the desired object is being manipulated.

The invention relates to evaluating a predetermined collision between a predetermined site (2) on the body of a living being and a predetermined object (1), comprising the steps of a) providing a 3D model of the predetermined object (1) on an arithmetic logic unit; b) providing a polygon mesh model of the predetermined site (2) on the body on an arithmetic logic unit, wherein each field Fij of the mesh of the polygon mesh model is square, and a stress-deformation characteristic curve (s) is predetermined for each field Fij of the mesh; c) aligning the provided 3D model and the provided polygon mesh model in a virtual space by means of the arithmetic logic unit, wherein the arrangement of the two models relative to one another corresponds to the relative arrangement of the object and the site on the body during the predetermined collision; d) gradually shifting the 3D model and the polygon mesh model into one another in a collision direction (K) determined by the predetermined collision, in the virtual space, by means of the arithmetic logic unit, wherein an impression image (AB) having impression pixels Pij is generated for each step k of the gradual shifting process and a respective pixel value Pw of the impression pixels Pij represents an impression depth of the 3D model in a field Fij of the mesh of the polygon mesh model that is assigned to the respective impression pixel Pij; e) determining the respective stress values for the impression pixels Pij for the or at least one of the impression images (AB, AB, AB) according to the stress-deformation characteristic curve (s) assigned to the corresponding field Fij and the respective pixel value Pw; f) calculating a force F acting on the predetermined site (2) on the body by adding up the products of the stress values determined for the impression pixels Pij with the surface areas Aij of the assigned fields Fij of the mesh, for the step k corresponding to the at least one impression image (AB, AB, AB); in order to rapidly and accurately evaluate any predeterminable collisions between sites on the bodies of living beings and any objects, in particular with regard to a risk of injury to an operator, for example.

A control device that outputs a command for a robot includes a machine learning device that learns a command for the robot. The machine learning device includes a state observation unit that observes a state of the robot and a state of a person present in a peripheral area of the robot, as state variables representing a current state of an environment, a determination data acquisition unit that acquires determination data representing an interference state between the robot and the person, and a learning unit that learns the state of the robot, the state of the person present in the peripheral area of the robot, and the command for the robot obtained by associating the state of the robot and the state of the person present in the peripheral area of the robot by using the state variables and the determination data.

Predefining a permissible maximum speed for a robotic device may include predefining a contact point between a human operator and the robotic device for a collision between the human operator and the robotic device, a geometry of the robotic device at the contact point, and a spatial boundary condition of the collision. The method may also include determining whether the collision is a clamp-free collision or a clamped collision using a computing unit. The method may also include calculating, by the computing unit, the permissible maximum speed of the robotic device at the contact point with a free-impact model, and with a clamping-impact model or with a quasi-static-clamping model. The method may also include using the computing unit to output a signal dependent on the calculated permissible maximum speed for the robotic device to predefine the permissible maximum speed of the robotic device.

A robotic system includes a jointed mechanism, position sensors, and a controller. The mechanism has an end-effector, and further includes actively-controlled joints and passive joints that are redundant with the actively-controlled joints. The position sensors are operable for measuring joint positions of the passive joints. The controller is in communication with the position sensors, and is programmed to execute a method to selectively control the actively-controlled joints in response to the measured joint positions using force control and/or a modeled impedance of the robotic mechanism. Possible control modes in impedance control include an Autonomous Mode in which an operator does not physically interact with the end-effector and a Cooperative Control Mode in which the operator physically interacts with the end-effector.

A human-collaborative robot system includes a first force detection section that detects external force acting on a robot; a second force detection section that detects only an operating force acting on the robot when a human manually operates the robot; and a safety assurance operation command section that, in the case where the external force detected by the first force detection section exceeds a predetermined threshold value, commands a safety assurance operation of causing the robot to move in a direction that reduces the external force or causing the robot to stop. When the human is manually operating the robot while the robot is in the stopped state, the safety assurance operation command section compares a value obtained by subtracting the operating force detected by the second force detection section from the external force detected by the first force detection section with a predetermined threshold value.

A human-robot cooperation (HRC) workstation has a programmable industrial robot (4) and a manual working area (14) for a worker (5) in a region surrounding the industrial robot (4). In the HRC workstation (1), the working areas of the industrial robot (4) and the worker (5) overlap. Contact between the worker (5) and the industrial robot (4) is possible. The workstation (1) is divided into a plurality of different zones (17, 18, 19, 20) having differently high levels of risk of hazard from the industrial robot (4) for the worker (5). The industrial robot (4) is suitable for human-robot cooperation.

A work assisting system includes a sensor unit that detects a position and an orientation of at least one body part of a worker; a supply unit that supplies a part or a tool to the worker; and a cell controller that controls the supply unit, the cell controller including a machine learning unit that constructs a model by learning a work status of the worker on the basis of the detected position and orientation, and a work status determining unit that determines the work status of the worker by using the constructed model. The supply unit selects the part or tool on the basis of the determined work status and changes the position and orientation of the part or tool on the basis of the position and orientation of the at least one body part.

A production system includes a robot, a robot controller, and a person detection part. The controller includes first speed comparison unit that has the function of activating a power cutoff unit so as to stop an operation of the robot when a current speed exceeds a predetermined reference speed; and an external-force comparison unit that has the function of activating the power cutoff unit so as to stop the operation of the robot when a current force applied to the robot exceeds a predetermined reference force. The controller disables the functions of the first speed comparison unit and the external-force comparison unit while the person detection part detects the absence of the operator in the cooperative operation space.