Unique systems, methods, techniques and apparatuses of a robot training system are disclosed. One exemplary embodiment is an industrial robot training system comprising a mixed reality display device structured to superimpose a virtual scene on a real-world view of a real-world scene including a plurality of physical objects including an industrial robot, a video input device, and a computing device. The computing device is structured to detect physical objects using video output from the video input device, generate virtual objects using the detected physical objects, simulate a virtual robot path, determine one movement of the series of robot movements causes a collision, adjust the virtual robot path so as to avoid the collision between the two virtual objects of the plurality of virtual objects, and program the industrial robot to perform a real robot path using the adjusted virtual robot path.

A system has a virtual-world (VW) controller and a physical-world (PW) controller. The pairing of a PW element with a VW element establishes them as corresponding physical and virtual twins. The VW controller and/or the PW controller receives measurements from one or more sensors characterizing aspects of the physical world, the VW controller generates the virtual twin, and the VW controller and/or the PW controller generates commands for one or more actuators affecting aspects of the physical world. To coordinate the corresponding virtual and physical twins, (i) the VW controller controls the virtual twin based on the physical twin or (ii) the PW controller controls the physical twin based on the virtual twin. Depending on the operating mode, one of the VW and PW controllers is a master controller, and the other is a slave controller, where the virtual and physical twins are both controlled based on one of VW or PW forces.

Specialized robot motion planning hardware and methods of making and using same are provided. A robot-specific hardware can be designed using a tool that receives a robot description comprising a collision geometry of a robot, degrees of freedom for each joint of the robot, and joint limits of the robot; receives a scenario description; generates a probabilistic roadmap (PRM) using the robot description and the scenario description; and for each edge of PRM, produces a collision detection unit comprising a circuit indicating all parts of obstacles that collide with that edge. The hardware is implemented as parallel collision detection units that provide collision detection results used to remove edges from the PRM that is searched to find a path to a goal position.

An external force torque due to a collision as a collision torque estimation value is estimated by subtracting a dynamic torque obtained by an inverse dynamic calculation of a robot from a torque output to a gear reducer by a motor. It is determined that the robot receives an external force if the collision torque estimation value is greater than a predetermined collision detection threshold.

A control apparatus for controlling operation of a work robot for performing work inside a target region using a manipulator includes a trajectory information acquiring unit for acquiring N1 or N pieces of trajectory information respectively indicating N1 or N trajectories connecting N work regions where the work robot performs a series of work operations in order of a series of work operations; a classifying unit for classifying the N1 or N trajectories as (i) trajectories that need correction or (ii) trajectories that do not need correction; and a trajectory planning unit for planning a trajectory of a tip of the manipulator between two work regions relating to the each of the one or more trajectories, for each of the one or more trajectories classified as a trajectory that needs correction by the classifying unit.

A teaching device constructs, in a virtual space, a virtual robot system in which a virtual 3D model of a robot and a virtual 3D model of a peripheral structure of the robot are arranged, and teaches a moving path of the robot. The teaching device includes an acquisition unit configured to acquire information about a geometric error between the virtual 3D models, and a correction unit configured to correct the moving path of the robot in accordance with the information acquired by the acquisition unit.

According to one embodiment, a monitor apparatus includes a memory and processing circuitry. The processing circuitry acquires first information indicating a position and a moving direction of a target, acquires second information indicating a position of each of moving objects and sensors which are provided in the moving objects, selects at least one of a first moving object for monitoring the target from among the moving objects or a first sensor for monitoring the target from among the sensors, based on the first information and the second information, and transmits third information indicating the target and at least one of the first moving object or the first sensor.

The invention relates to a method of collision handling for a robot with a kinematic chain structure comprising at least one kinematic chain, wherein the kinematic chain structure includes: a base, links, joints connecting the links, actuators and at least one end-effector, a sensor S.sub.distal.i in the most distal link of at least one of the kinematic chains for measuring/estimating force/torque, and sensors S.sub.i for measuring/estimating proprioceptive data, wherein the sensors S.sub.i are arbitrarily positioned along the kinematic chain structure, the method including: providing a model describing the dynamics of the robot; measuring and/or estimating with sensor S.sub.distal.i force/torque F.sub.ext,S.distal.i in the most distal link of at least one of the kinematic chains; measuring and/or estimating with the sensors S.sub.i proprioceptive data: base and robot generalized coordinates q(t) and their time derivative {dot over (q)}(t), generalized joint motor forces .sub.m, external forces F.sub.S, a base orientation .sub.B(t) and a base velocity {dot over (x)}(t).sub.B; generating an estimate {circumflex over ()}.sub. of the generalized external forces .sub.ext with a momentum observer based on at least one of the proprioceptive data and the model; generating an estimate {umlaut over ({circumflex over (q)})}(t) of a second derivative of base and robot generalized coordinates {umlaut over (q)}(t), based on {circumflex over ()}.sub. and .sub.m; estimating a Cartesian acceleration {umlaut over ({circumflex over (x)})}.sub.D of point D on the kinematic chain structure based on {umlaut over ({circumflex over (q)})}(t); compensating the external forces F.sub.D for rigid body dynamics effects based on {umlaut over ({circumflex over (x)})}.sub.D and for gravity effects to obtain an estimated external wrench {circumflex over (F)}.sub.ext,S.i; compensating {circumflex over ()}.sub. for the Jacobian J.sub.S.distal.i.sup.T transformed F.sub.ext,S.distal.i to obtain an estimation {circumflex over ()}.sub.ext,col of generalized joint forces originating from unexpected collisions; detecting a collision based on given thresholds .sub.thresh and F.sub.S.i,thresh if {circumflex over ()}.sub.ext,col>.sub.thresh and/or if {circumflex over (F)}.sub.ext,S.i>F.sub.S.i,thresh.

An interference avoidance device is provided with: a three-dimensional sensor that is attached to a tip portion of a robot arm and acquires a distance image of an area around a robot; a position data creating portion that converts coordinates of a nearby object in the distance image to coordinates on a robot coordinate system and creates the position data of the nearby object based on the coordinates of the nearby object on the robot coordinate system; a storage portion that stores the position data; and a control portion that controls the robot based on the robot coordinate system; and the control portion controls the robot to avoid interference of the robot with the nearby object, based on the position data stored in the storage portion.

A teaching device constructs, in a virtual space, a virtual robot system in which a virtual 3D model of a robot and a virtual 3D model of a peripheral structure of the robot are arranged, and teaches a moving path of the robot. The teaching device includes an acquisition unit configured to acquire information about a geometric error between the virtual 3D models, and a correction unit configured to correct the moving path of the robot in accordance with the information acquired by the acquisition unit.