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Smart Sensor-Based Robot Control and Calibration
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Smart Sensor-Based Robot Control and Calibration

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 7974

Special Issue Editors

Prof. Dr. Alexandr Klimchik

E-Mail Website
Guest Editor
Institute of Robotics and Computer Vision, Innopolis University, Innopolis, Russia
Interests: industrial robotics; intelligent robotic systems; human–robot interaction; robot calibration; compensation positioning errors; stiffness modeling; cable-driven robots
Prof. Dr. Igor Gaponov

E-Mail Website
Guest Editor
Institute of Robotics and Computer Vision, Innopolis University, Innopolis, Russia
Interests: robotics; control theory; nonlinear control; exoskeletons; novel actuators

Special Issue Information

Dear Colleagues,

Sensor-based control of different robotics systems is one of the main challenges of modern robotics, pushing us to develop intelligent robots which work, move, and interact with us. Contemporary robots are being equipped with new sophisticated sensors, measuring information about the world both directly and indirectly. In addition, readily available, redundant sensor information may provide us with additional information on the robot’s state and behavior. This offers robots huge potential for further enhancement of their intelligent control systems and parameter calibration using both classical and AI-based approaches. This Special Issue will highlight state-of-the-art sensor technology in applications to the area of “Smart Sensor-Based Robot Control and Calibration” through original contributions and reviews.

Topics of interest include but are not limited to the following:

  • Smart sensor design and application for various robotics directions;
  • Sensor fusion and parameter space augmentation in robotic applications;
  • Real-time intelligent control of robotic systems with advanced sensing capabilities;
  • Multilevel control for robotic systems with redundant sensing;
  • Real-time state estimation using indirect measurements;
  • Advanced control for robotic systems based on redundant sensing;
  • Smart interaction in robotic application with advanced sensing;
  • Learning-based intelligent control;
  • Advanced robot calibration.

Prof. Dr. Alexandr Klimchik
Prof. Dr. Igor Gaponov
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Robotics 
  • Intelligent control
  • Robot calibration 
  • Sensor fusion 
  • Real-time control 
  • Multilevel control 
  • Smart interacting 
  • Learning-based control

Published Papers (3 papers)

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Research

19 pages, 3404 KiB  
Article
Development and Experimental Studies of an Identification Method of Kinematic Parameters for Industrial Robots without External Measuring Instruments
by Anton Gubankov and Dmitry Yukhimets
Sensors 2022, 22(9), 3376; https://doi.org/10.3390/s22093376 - 28 Apr 2022
Cited by 6 | Viewed by 1603
Abstract
This paper proposes a method for the identification of kinematic parameters of multilink series industrial robots, which does not require the use of complex and expensive equipment for high-precision external measurements of the position and orientation of an end effector in a Cartesian [...] Read more.
This paper proposes a method for the identification of kinematic parameters of multilink series industrial robots, which does not require the use of complex and expensive equipment for high-precision external measurements of the position and orientation of an end effector in a Cartesian coordinate system. This method, by means of simple and affordable tools, enables us to achieve a significantly increased accuracy of movement of end effectors in serial robots performing various technological operations. The proposed method is experimentally verified and can be applied directly in production lines. Full article
(This article belongs to the Special Issue Smart Sensor-Based Robot Control and Calibration)
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25 pages, 6439 KiB  
Article
Fast Kinematic Re-Calibration for Industrial Robot Arms
by Sreekanth Kana, Juhi Gurnani, Vishal Ramanathan, Sri Harsha Turlapati, Mohammad Zaidi Ariffin and Domenico Campolo
Sensors 2022, 22(6), 2295; https://doi.org/10.3390/s22062295 - 16 Mar 2022
Cited by 12 | Viewed by 4297
Abstract
Accurate kinematic modelling is pivotal in the safe and reliable execution of both contact and non-contact robotic applications. The kinematic models provided by robot manufacturers are valid only under ideal conditions and it is necessary to account for the manufacturing errors, particularly the [...] Read more.
Accurate kinematic modelling is pivotal in the safe and reliable execution of both contact and non-contact robotic applications. The kinematic models provided by robot manufacturers are valid only under ideal conditions and it is necessary to account for the manufacturing errors, particularly the joint offsets introduced during the assembling stages, which is identified as the underlying problem for position inaccuracy in more than 90% of the situations. This work was motivated by a very practical need, namely the discrepancy in terms of end-effector kinematics as computed by factory-calibrated internal controller and the nominal kinematic model as per robot datasheet. Even though the problem of robot calibration is not new, the focus is generally on the deployment of external measurement devices (for open loop calibration) or mechanical fixtures (for closed loop calibration). On the other hand, we use the factory-calibrated controller as an ‘oracle’ for our fast-recalibration approach. This allows extracting calibrated intrinsic parameters (e.g., link lengths) otherwise not directly available from the ‘oracle’, for use in ad-hoc control strategies. In this process, we minimize the kinematic mismatch between the ideal and the factory-calibrated robot models for a Kinova Gen3 ultra-lightweight robot by compensating for the joint zero position error and the possible variations in the link lengths. Experimental analysis has been presented to validate the proposed method, followed by the error comparison between the calibrated and un-calibrated models over training and test sets. Full article
(This article belongs to the Special Issue Smart Sensor-Based Robot Control and Calibration)
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12 pages, 407 KiB  
Communication
Fault Identification in Electric Servo Actuators of Robot Manipulators Described by Nonstationary Nonlinear Dynamic Models Using Sliding Mode Observers
by Alexander Zuev, Alexey N. Zhirabok, Vladimir Filaretov and Alexander Protsenko
Sensors 2022, 22(1), 317; https://doi.org/10.3390/s22010317 - 01 Jan 2022
Cited by 2 | Viewed by 1323
Abstract
The problem of fault identification in electric servo actuators of robot manipulators described by nonstationary nonlinear dynamic models under disturbances is considered. To solve the problem, sliding mode observers are used. The suggested approach is based on the reduced order model of the [...] Read more.
The problem of fault identification in electric servo actuators of robot manipulators described by nonstationary nonlinear dynamic models under disturbances is considered. To solve the problem, sliding mode observers are used. The suggested approach is based on the reduced order model of the original system having different sensitivity to faults and disturbances. This model is realized in canonical form that enables relaxing the limitation imposed on the original system. Theoretical results are illustrated by practical example. Full article
(This article belongs to the Special Issue Smart Sensor-Based Robot Control and Calibration)
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