Classifications

• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
  • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
  • B25J9/00—Programme-controlled manipulators
  • B25J9/16—Programme controls
  • B25J9/1674—Programme controls characterised by safety, monitoring, diagnostic
  • B25J9/1676—Avoiding collision or forbidden zones
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B2219/00—Program-control systems
  • G05B2219/30—Nc systems
  • G05B2219/37—Measurements
  • G05B2219/37624—Detect collision, blocking by measuring change of velocity or torque
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B2219/00—Program-control systems
  • G05B2219/30—Nc systems
  • G05B2219/39—Robotics, robotics to robotics hand
  • G05B2219/39355—Observer, disturbance observer
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B2219/00—Program-control systems
  • G05B2219/30—Nc systems
  • G05B2219/40—Robotics, robotics mapping to robotics vision
  • G05B2219/40201—Detect contact, collision with human
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B2219/00—Program-control systems
  • G05B2219/30—Nc systems
  • G05B2219/41—Servomotor, servo controller till figures
  • G05B2219/41387—Observe reference torque, position and feedback position, estimate contact force

Definitions

• the present invention relates to a method and a system for controlling a robot as well as a robot arrangement with the system and a
• robot-assisted sonography it may be desirable to detect a contact of the robot or robotic medical device and then provide a force feedback to a haptic input device of the robot.
• Robotics May 9, 2014, propose two different methods for collision detection of robots: a method determines a fuzzy inference system ("Fuzzy inference system", FIS) from a position error, a commanded speed and the measured at joints
• FIS fuzzy inference system
• an autoregressive model (“AutoRegressive" AR)
• AutoRegressive AR detects joint torques, where a collision is detected based on a deviation of the joint predicted from the AR from the measured joint torques.
• the object of the present invention is to control a robot
• Claims 7 to 9 provide a system or computer program product
• a method for controlling a robot comprises the steps:
• a collision of a robot can advantageously be detected in one embodiment.
• a model-based determined external force resulting from an external load of the robot instead of a measured G (eticiang) elenkkraft detection can be improved, in particular by a fuzzy system, which then no longer the functionality of a model for determining the external force must comply with.
• the robot has at least six, in particular at least seven, actuatable or actuated joints.
• a medical application of the robot it carries a medical instrument, in particular an ultrasound head or the like.
• an anti-parallel force pair or torque is generally referred to herein as a force.
• a force in particular the determined collision force, the model-based determined external force and / or a feedback force explained below, can in particular be a Cartesian force with components in one or more Cartesian directions, in particular one Inertial or robot base fixed or robot end-member fixed coordinate system include, in particular.
• a position error depends on a deviation between an actual, in particular measured, pose of the robot and a desired, in particular commanded, pose of the robot, in particular of one
• Deviation between an actual position and a desired position and / or orientation of a robot-fixed reference, in particular of the TCP, can in particular indicate or be the deviation.
• a pose of the robot depends on the position of its joints, in particular drives, and / or the position and / or orientation of a robot-fixed reference, in particular of the TCP, it can indicate or be particular. Generalizing is thus present for a more compact representation
• a speed of the robot depends on the speed of its joints, in particular drives, and / or the
• a speed of a robot-fixed reference is also understood here to be the speed of the robot.
• the method in particular its step, comprises one
• Components of the model-based determined external force (respectively) one or more, in particular at least two, in particular at least three, degrees of membership of one or more components of the position error of the robot and (respectively) one or more, in particular at least two, in particular at least three, degrees of affiliation one or more Components of the pose and / or velocity of the robot based on a fuzzy set or membership functions of a fuzzy system;
• the system in particular its means for determining a collision force, in one embodiment:
• a degree of affiliation can in a conventional manner based on a
• Membership function of the fuzzy system can be determined.
• the component (s) of the model-based determined external force the component (s) of the model-based determined external force
• Pose / velocity assign a degree of affiliation to a first fuzzy set, eg "small” and a further degree of affiliation to a second fuzzy set, eg "large”, optionally also one or more further degrees of membership to further fuzzy sets, eg "medium” or similar
• the fuzzy system is an FIS ("fuzzy inference system"), in particular Sugeno or Mamdani.
• FIS fuzzy inference system
• it includes the membership functions that map or fuzzify the input values to degrees of membership, rules, or a rule base, respectively
• the FIS evaluates its output by weighting the rule base with the degrees of membership, and then weighting it into a different fuzzy set
• the defuzzification is carried out by means of the weighting of the rule base and by means of the evaluation of a linear function of the input variables.
• a component of the collision force in at least a first direction is dependent on one or more
• Determining at least one component of the collision force means for determining a component of the collision force in at least a first direction (respectively) depending on one or more degrees of membership of a component of the model-based determined external force in this first direction, one or more degrees of membership of a component the position error of the robot in this first direction and / or one or more degrees of membership of a position of a robot-fixed reference in this first direction.
• a first direction may in particular be a robot (member) or space-fixed and / or Cartesian direction, in particular of the working space of the robot.
• a first direction is the vertical direction, a horizontal direction, or a direction inclined to the vertical and horizontal.
• a first direction is a collision direction, in particular an anticipated and / or main collision direction, and / or perpendicular to a potential, in particular predetermined, collision plane.
• a collision direction in particular an anticipated and / or main collision direction, and / or perpendicular to a potential, in particular predetermined, collision plane.
• the vertical is the expected main collision direction. It has been found that for a favorable determination of a component of the collision force in certain directions, in particular in one
• a component of the collision force in at least one second direction is one or more depending on one or more degrees of membership of a component of the model-based determined external force in that second direction
• the system or its means for determining at least one component of the collision force additionally or alternatively comprises means for determining a component of the collision force in at least one second direction (respectively) in dependence on one or more
• (Main) collision direction advantageously in addition to the position error and the component of the external force, the speed of a robot-fixed reference in this, in particular to the (main) direction of collision inclined direction is particularly suitable.
• the second direction may in particular be a robot (member) or space-fixed and / or Cartesian direction, in particular of the working space of the robot.
• the second direction is a horizontal direction, the vertical direction, or a direction inclined to the vertical and horizontal.
• the second direction is inclined to the first direction, in particular perpendicular to this.
• two second directions are perpendicular to each other and / or two first directions perpendicular to each other.
• the fuzzy system in particular one or more of its membership functions and / or rules and / or its linear function, is or are parameterized by means of a neural network, in particular based on the method of the smallest error rate and / or the method the reverse propagation descending gradient.
• the system comprises means for parameterizing the fuzzy system, in particular one or more of its membership functions and / or rules, by means of a neural network, in particular based on the method of the smallest error rate and / or the method of
• the method or system can advantageously be adapted to different robots and / or applications, in particular rapidly, autonomously and / or robustly.
• the external force is modeled based on a
• dynamic model of the robot Accordingly includes in one
• the driving forces T mot and / or the vector q and its time derivatives can be detected or detected in particular by means of sensors.
• a (time) predictive model in particular an autoregressive model, can be used.
• an AR model be provided to determine the external forces modeled.
• a time delay through the fuzzy system can be compensated for, at least partially.
• the external force is determined on the basis of a predictive model, in particular an autoregressive model.
• the system comprises means for model-based determination of the external force on the basis of a predictive model, in particular an autoregressive
• the predictive model in one embodiment, forms an external force, determined in one embodiment based on the dynamic model, on one
• a feedback force is determined after detecting a collision of the robot without the fuzzy system and / or the predictive model based on, in particular the same, dynamic model of the robot.
• the system includes means for switching upon detection of a collision based on the collision force to another determination to determine a feedback force, or means for determining a feedback force after detecting a collision of the robot without Fuzzy system and / or the predictive model based on, in particular the same, dynamic model of the robot.
• the feedback force is a feedback force of a haptic input device of the robot or a force, which is impressed on an operating element of an input device of the robot, in particular by at least one actuator, in order to force the operator a contact of the robot,
• the system or the robot assembly includes a haptic input device and means for applying the feedback force to an operating element of the input device to force feedback to a user a contact of the robot, in particular a guided by this tool, in particular medical instrument mediate, on.
• Feedback force without fuzzy system and / or predictive model in one embodiment advantageously distortions, in particular filtering, the force that can be useful for detecting a collision, reduced, and so a force feedback can be improved.
• the feedback force prior to detecting a collision of the robot, the feedback force may be at least substantially equal to zero based on the determined collision force. Also, this can be a force feedback can be improved.
• the feedback force in an embodiment prior to detecting a collision of the robot can also be determined on the basis of the determined collision force, in particular corresponding thereto.
• a means in the sense of the present invention may be designed in terms of hardware and / or software, in particular a data or signal-connected, in particular digital, processing, in particular microprocessor unit (CPU) and / or a memory and / or bus system or multiple programs or program modules.
• the CPU may be configured to execute instructions implemented as a program stored in a memory system, to capture input signals from a data bus, and / or
• a storage system may comprise one or more, in particular different, storage media, in particular optical, magnetic, solid state and / or other non-volatile media.
• the program may be such that it is capable of embodying or executing the methods described here, so that the CPU can carry out the steps of such methods and thus, in particular, operate the robot or
• one or more of the steps described herein are at least partially automated, in particular by the system or means described herein.
• the invention is particularly in medical applications in which a robot-guided medical instrument temporarily contacts a patient, particularly in robot-assisted sonography or other imaging
• FIG. 1 shows a robot arrangement with a robot and a system for controlling the robot according to an embodiment of the present invention
• FIG. 1 shows a robot arrangement with a robot 30, which carries an ultrasound head 31, and a system for controlling the robot 30 or a medical application of the robot in the form of a robot controller 10, which communicates with a haptic input device 20 for controlling the robot 30 respectively.
• the robot controller 10 executes a method explained below with reference to FIGS. 1, 2 according to an embodiment of the present invention and has a corresponding computer program product for this purpose.
• a first step S10 the controller 10 determines joint angles and
• the ones from the dynamic model are based on the joint angles and their time derivatives
• this external force F e determined on the basis of the dynamic model 1 1 is determined by an ARMA model 12
• model-based predictive determines an external force [F 'ex, F' E, Y, F 'ez] resulting from an external stress of the robot 30th
• step S30 in the subsystems 13X, 13Y also for horizontal components ⁇ , Ay of a position error and horizontal
• step S30 in the subsystem 13Z also for a vertical component Az of the position error and a vertical component z of a position of the TCP of the robot 30 are respectively based on
• Component F cz or horizontal components F cx , F cy of a collision force Component F cz or horizontal components F cx , F cy of a collision force.
• the rules and / or membership functions Bi of the fuzzy system 13 are parameterized in advance by a neural network. As long as the thus determined collision force [F cx , F cy , F c , 2 ] remains below a predetermined threshold, a switching means 14 of the controller 10 in a step S50 to the haptic input device 20, a feedback force F ⁇ equal to zero , alternative
• the collision force [F c , x , F c, y , F c , z ] thus determined can also be output to the haptic input device 20 itself as a feedback force F ft .
• the switching means 14 to the haptic input device 20 in step S50 a feedback force F «, which determines the controller 10 based on the dynamic model 1 1 without the predictive model 12 or the fuzzy system 13, in a simple Case directly the external force F e . It can also output a corresponding, for example optical and / or acoustic, signal
• the switching means 14 switches back again and the controller 10 detects the next collision of the ultrasonic head 31 in the manner described above.

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• Engineering & Computer Science (AREA)
• Robotics (AREA)
• Mechanical Engineering (AREA)
• Manipulator (AREA)

Applications Claiming Priority (2)

Publications (1)

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ID=56550828

Family Applications (1)

Country Status (3)

Families Citing this family (5)

Family Cites Families (8)

• 2015
  • 2015-07-30 DE DE102015009892.6A patent/DE102015009892A1/de not_active Withdrawn
• 2016
  • 2016-07-11 WO PCT/EP2016/001195 patent/WO2017016641A2/fr active Application Filing
  • 2016-07-11 EP EP16744303.5A patent/EP3328595A2/fr not_active Withdrawn

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