A method for controlling vibration of flexible mechanical arms based on cooperative tracking is disclosed, including: building a dynamic model of the flexible mechanical arm, according to a dynamic characteristic, constructing a flexible mechanical arm group made up of a plurality of flexible mechanical arms, assigning one of the plurality of flexible mechanical arms as a leader and the rest ones as followers which are required to track the leader's motion trajectory so as to realize cooperative work; designing cooperative control-based boundary controllers in combination with a Lyapunov method to realize cooperative work and suppress vibration of the flexible mechanical arms; and constructing a Lyapunov function using Lyapunov direct method to validate stability of the flexible mechanical arms under the control.

A robot control method, and associated robot controllers and robots operating with such methods and controllers, providing real-time vibration suppression. The control method involves learning to support real-time, vibration-suppressing control. The method uses state-of-the-art machine learning techniques in conjunction with a differentiable dynamics simulator to yield fast and accurate vibration suppression. Vibration suppression using offline simulation approaches that can be computationally expensive may be used to create training data for the controller, which may be provide by a variety of neural network configurations. In other cases, sensory feedback from sensors onboard the robot being controlled can be used to provide training data to account for wear of the robot's components.

A conveying apparatus that facilitates setting of an operation mode and setting of appropriate conditions during teaching is provided. An input determination section determines whether or not a combination of a conveyable weight and an operation mode input from an input portion is appropriate. A motor parameter determination section determines one or more motor parameters of at least one servoamplifier for one or more servomotors based on the operation mode and the conveyable weight determined as appropriate by the input determination section. The one or more motor parameters include a maximum speed and a maximum acceleration of the one or more servomotors. A parameter change section allows a speed and an acceleration of the one or more servomotors to be changed up to the maximum speed and the maximum acceleration, respectively.

Input shapers for control inputs to the robotic surgical system and their method of controlling a linkage of a robot with a controller includes receiving a desired joint angle of a joint of the robot; and transmitting a first control signal to a motor to actuate the joint in response to a desired joint velocity, the desired joint velocity being a function of the desired joint angle and a current joint angle of the joint.

A system providing dynamic balancing in a robotic system. The system includes memory storing a definition of a robot and storing an input animation for the robot specifying motion of components of the robot. A simulator performs a dynamic simulation of the robot performing the input animation including modeling a first set of the components as flexible components and a second set of the components as rigid components. Each of the flexible components is coupled at opposite ends to one of the rigid components. An optimizer generates a retargeted motion for the components to provide dynamic balancing of the robot performing the retargeted motion. The optimizer generates the retargeted motion by transforming forces acting on the robot to a local contact frame rigidly moving with the robot. The optimizer generates the retargeted motion so a zero-moment point of the robot lies in a support area of the robot's feet.

A method for controlling movement of a robot having a plurality of links connected by rotatably driven joints includes the steps of: a) defining a target speed vector of a reference point of the robot in Cartesian space; b) determining rotation speeds ({dot over (q)}.sub.ref) of the joints which minimize a weighted sum, the weighted sum having for summands i) a discrepancy (∥{dot over (x)}.sub.ref.sup.k−J{dot over (q)}.sub.ref.sup.k∥.sub.W.sub.x) between the target speed vector ({dot over (x)}.sub.ref) and an actual speed vector ({dot over (x)}.sub.act) calculated from actual rotation speeds of the joints; and ii) a rate of change $\left(\frac{1}{T_S}{.Math.{\stackrel{.}{q}}_{\mathrm{ref}}^k-{\stackrel{.}{q}}_{\mathrm{ref}}^{k-1}.Math.}_{W_a}\right)$
of the target rotation speeds; and c) setting the rotation speeds ({dot over (q)}.sub.ref) determined in step (b) as target rotation speeds of the joints.

An abnormality detection method for detecting an abnormality of an encoder provided for a robot includes: obtaining corrected position information according to commanded position information output from a controller that designates the rotational position of a motor and an output signal output from the encoder; and, determining, after comparing the corrected position information with the detected position information according to the output signal output from the encoder, the abnormality of the encoder, if there is a difference greater than or equal to a predetermined value between the corrected position information and the detected position information. The controller removes a vibration component of the robot corresponding to the weight of an attachment load from the commanded position information and compensates for a time delay to obtain the corrected position information.

A robot system includes: a learning control unit configured to perform learning for calculating a learning correction amount for bringing a position of a control target portion toward a target position; a robot control unit configured to control the operation of the robot mechanism unit; a power spectrum calculating unit configured to calculate a power spectrum of a vibration data of the control target portion; a comparison unit configured to compare each power spectrum between at the time of the current learning and at the time of the immediately preceding learning; and a learning correction amount updating unit configured to adjust at least one of a phase and a gain of the learning correction amount used at the time of the current learning to set the adjusted learning correction amount as a new learning correction amount used at the time of next learning.

A robot system includes a work apparatus, a robot, and control circuitry. The work apparatus is configured to move a work module relatively to the work apparatus. The work module is configured to perform work. The work apparatus is connected the robot. The control circuitry is configured to control the robot to move so as to reduce a force generated by moving the work module by the work apparatus.

a speed reducer angular transmission error identification system including a variation data acquisition unit that acquires first variation data indicating a periodic variation of an operation of a second joint caused by a first motor's angular transmission error when a first joint control unit rotates a first motor's output shaft in a first direction at a constant first target speed and a second joint drive unit rotates an output shaft of a second motor at a constant second target speed, second variation which is data indicating a periodic variation of an operation of second joint caused by the first motor's angular transmission error when the first joint control unit rotates the first motor's output shaft in a second direction at the constant first target speed and the second joint control unit rotates the second motor's output shaft at the constant second target speed.