An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning

Guler, Berk; Niaz, Pouya P.; Madani, Alireza; Aydın, Yusuf; Başdoğan, Çağatay

doi:10.1016/j.mechatronics.2022.102851

Cited by 11 publications

(2 citation statements)

References 54 publications

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“…It is noteworthy that transition of damping values follows a ramp profile with a length of 1 second. Using the analysis conducted in our earlier work [23] we observed that this will not lead to instability of the pHRI system. The values used for admittance damping in this study are tabulated in Table I.…”

Section: F Admittance Adaptationmentioning

confidence: 84%

Robot-Assisted Drilling on Curved Surfaces with Haptic Guidance under Adaptive Admittance Control

Madani¹,

Niaz²,

Guler³

et al. 2022

Preprint

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Drilling a hole on a curved surface with a desired angle is prone to failure when done manually, due to the difficulties in drill alignment and also inherent instabilities of the task, potentially causing injury and fatigue to the workers. On the other hand, it can be impractical to fully automate such a task in real manufacturing environments because the parts arriving at an assembly line can have various complex shapes where drill point locations are not easily accessible, making automated path planning difficult. In this work, an adaptive admittance controller with 6 degrees of freedom is developed and deployed on a KUKA LBR iiwa 7 cobot such that the operator is able to manipulate a drill mounted on the robot with one hand comfortably and open holes on a curved surface with haptic guidance of the cobot and visual guidance provided through an AR interface. Real-time adaptation of the admittance damping provides more transparency when driving the robot in free space while ensuring stability during drilling. After the user brings the drill sufficiently close to the drill target and roughly aligns to the desired drilling angle, the haptic guidance module fine tunes the alignment first and then constrains the user movement to the drilling axis only, after which the operator simply pushes the drill into the workpiece with minimal effort. Two sets of experiments were conducted to investigate the potential benefits of the haptic guidance module quantitatively (Experiment I) and also the practical value of the proposed pHRI system for real manufacturing settings based on the subjective opinion of the participants (Experiment II). The results of Experiment I, conducted with 3 naive participants, show that the haptic guidance improves task completion time by 26% while decreasing human effort by 16% and muscle activation levels by 27% compared to no haptic guidance condition. The results of Experiment II, conducted with 3 experienced industrial workers, show that the proposed system is perceived to be easy to use, safe, and helpful in carrying out the drilling task.

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Section: F Admittance Adaptationmentioning

confidence: 84%

Robot-Assisted Drilling on Curved Surfaces with Haptic Guidance under Adaptive Admittance Control

Madani¹,

Niaz²,

Guler³

et al. 2022

Preprint

Self Cite

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“…Construction [31,32] They can be used in construction to perform tasks such as welding, drilling, and painting. Multiple arms can work together to perform these tasks on a larger scale or in a shorter time frame.…”

Section: Types Specific Applicationsmentioning

confidence: 99%

Cooperative Robot Manipulators Dynamical Modeling and Control: An Overview

Ghorbanpour

2023

Dynamics

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Robot manipulators possess the capability to autonomously execute complex sequences of actions. Their proficiency in handling challenging and hazardous tasks has led to their widespread adoption across diverse sectors, including industry, business, household appliances, rehabilitation, and many more. However, certain tasks prove to be challenging for individual robots, primarily due to constraints in their structure and limited degrees of freedom. Cooperative robot manipulators (CRMs) emerge as a compelling solution when dealing with large, heavy, or flexible payloads. The utilization of CRMs offers a host of benefits, including enhanced manipulation performance achieved through the synergy of sensing and actuation capabilities or by tapping into increased redundancy. Numerous techniques have been devised for the control and dynamical modeling of CRMs. Nevertheless, the field continues to present technical challenges and scientific inquiries. To inspire and facilitate further research and development in this realm, this review aims to consolidate the current body of knowledge pertaining to CRMs kinematics, dynamics modeling, and various control methodologies used for payload manipulation via CRMs.

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