Analyzing the Methods Identification Shaft Position in Active Robotic Assembly of “Shaft-Sleeve” Joints with Chamfer Contact

Vartanov, M. V.; Petrov, V. K.; Nguyễn, Vân Dung; Tran, Dinh Van

doi:10.1007/978-981-16-3844-2_16

Cited by 3 publications

(1 citation statement)

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“…Using inputs from a force-torque sensor, experimental studies of the assemblability of shaft-sleeve type joints during robotic assembly are described in works [15][16][17]. In the study [18][19][20], mathematical models based on information from the force-torque sensor were provided at the contact stages of shaft-sleeve type joints during the assembly of robots. In the context of the strategy implementation, the principle of proactive adaptive control using force-torque sensors for force and position control is widely used.…”

Section: Introductionmentioning

confidence: 99%

Intelligent control algorithm for industrial robots when performing the assembly operation of cylindrical non-rigid parts

Vartanov,

Nguyen,

Kogan

et al. 2024

Preprint

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When developing robotic assembly technology, it is necessary to use intelligent algorithms that control the assembly process online. One of the tasks that has been little studied so far is the assembly of cylindrical non-rigid parts. Mathematical models of the coupling stages during robotic assembly have been developed, which are necessary for the identification of the signals of the force-torque sensor. The obtained analytical solutions make it possible to determine the conditions for the occurrence of jamming of the non-rigid shaft during two-point contact during the coupling of the shaft with a rigid sleeve. The obtained values of deflections and angles of rotation allow us to correct the movement of the output link of the robot during the assembly operation. A mathematical model is presented for solving the problem of determining the current contact state (CS) during assembly using the support vector machine (SVM) method when obtaining information about the position coordinates by the control system of an industrial robot and forces from a force-torque sensor. The algorithm was tested on an IRB-140 industrial robot with an IRC5 controller equipped with an FTN-AXIA80 SI500-20 Ethernet force-torque sensor from Schunk.

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