Autonomous Transport Mean Reverse Movement Control by Nodal Points

Michael Rachkov; Sergey Petukhov

doi:doi:10.11648/j.ajetm.20190405.11

| Peer-Reviewed

Autonomous Transport Mean Reverse Movement Control by Nodal Points

Michael Rachkov, Sergey Petukhov

Published in American Journal of Engineering and Technology Management (Volume 4, Issue 5)

Received: 20 September 2019 Accepted: 21 September 2019 Published: 22 November 2019

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

The study presents an exact formulation of control for the reverse moving a transport mean along a polygonal course consisting of rectilinear segments interconnected by nodal points. Appropriateness of the question is caused by the need to figure out a several of tasks: to secure the transport mean in the occasion of а communication crash by returning along the course already passed, to escape rotation in constrained or unsafe conditions, or partial go back for the following avoid of the hurdle and continuation of the forward motion. The control method of forward motion assumes that the route of movement is predetermined, and the path is elaborated by using landmarks. Video cameras are placed on the transport mean for landmark measurement. They are controlled by the operator through the radio channel. Errors in estimating deviation from the supposed course are detected using the multidimensional correlation investigation instrument based on the dynamics of a lateral deviation mistake and a velocity mistake. Reception algorithm of the information is presented on reference points. The outcome of the test showed a considerable preciseness in determining the position vector that provides the reverse movement relative to the reference course with a reasonably admissible mistake while returning to the start spot.

Published in	American Journal of Engineering and Technology Management (Volume 4, Issue 5)
DOI	10.11648/j.ajetm.20190405.11
Page(s)	73-78
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Automatic Control, Reverse Motion, Navigation, Landmarks, Correlation Analysis, Reference Trajectory

References

[1]	L. Thrybom, J. Neander, E. Hansen, and K. Landernas. Future challenges of positioning in underground mines. In Proceedings of the IFAC Conference on Embedded Systems, Computer Intelligence and Telematics, pp. 222–226, June 2015.
[2]	T. Nothdurft, P. Hecker, S. Ohl, F. Saust, M. Maurer, A. Reschka, and J. Bohmer. Stadtpilot: First fully autonomous test drives in urban traffic. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 919–924, October 2011.
[3]	S. Petukhov, M. Rachkov. Navigation Method of Autonomous Robot Backward Motion by Remembered Landmarks // 12th Int. Conf. on Climbing and Walking Robots and the Support Technologies for Mobile Machines. - 2009. - pp. 19-25.
[4]	M. Rachkov, S. Petukhov, Navigation of the autonomous vehicle reverse movement, Journal of Physics: Conference Series, V. 315 (2018) 012019 doi: 10.1088/1757-899X/315/1/012019, pp. 1-7, 2019.
[5]	S. Lefèvre, D. Vasquez, and C. Laugier. A survey on motion prediction and risk assessment for intelligent vehicles. Robomech Journal, 1 (1): 1, 2014.
[6]	R. Attia, R. Orjuela, and M. Basset. Combined longitudinal and lateral control for automated vehicle guidance. Vehicle System Dynamics, 52 (2): 261–279, 2014.
[7]	J. Kong, M. Pfeiﬀer, G. Schildbach, and F. Borrelli. Kinematic and dynamic vehicle models for autonomous driving control design. In Proceedings of the IEEE Intelligent Vehicles Symposium, pp. 1094–1099, June 2015.
[8]	V. Turri, A. Carvalho, E. Tseng, K. Johansson, and F. Borrelli. Linear model predictive control for lane keeping and obstacle avoidance on low curvature roads. Proceedings of the International IEEE Intelligent Transportation Systems Conference, pp. 378–383, October 2013.
[9]	C. Beal and J. Gerdes. Model predictive control for vehicle stabilization at the limits of handling. IEEE Transactions on Control Systems Technology, 21 (4): 1258–1269, 2013.
[10]	A. Carvalho, Y. Gao, S. Lefevre, and F. Borrelli. Stochastic predictive control of autonomous vehicles in uncertain environments. Proceedings of the International Symposium on Advanced Vehicle Control, September 2014.
[11]	F. Borrelli, A. Bemporad, and M. Morari. Predictive control for linear and hybrid systems. 2015. 440 p.
[12]	DeSouza G. N., Kak A. S. Vision for Mobile Robot Navigation // IEEE Trans. on PAMI. - 2002. - № 24. - P. 237-267.
[13]	Petukhov S. V., Ivaniugin V. M. Interaction with external environment of robot by man-machine interface // Proceedings of the 2nd Inter. Conf. On Climbing and Walking Robots, - 1999. – pp. 445-452.
[14]	Petuhov A. S., Rachkov M. Ju., Petuhov S. V. Application of compressed image post-processing algorithms for remote control of mobile robots // Mechatronics, automation, control. - 2007. - №1. - pp. 17-24 (in Russian).
[15]	Measuring systems of a robotic complex for operation in a nuclear reactor / Gradeckij V. B., Rachkov M. Ju., Petuhov S. V., et al. - Preprint № 656. – Russian Academy of Sciences, 1999. - 46 p. (in Russian).
[16]	K. Wurm, A. Hornung, M. Bennewitz, C. Stachniss, and W. Burgard. Octomap: A probabilistic, ﬂexible, and compact 3D map representation for robotic systems. In Proceedings of the IEEE Conference on Robotics and Automation, vol. 2, May 2010.

Cite This Article

Plain Text BibTeX RIS

APA Style

Michael Rachkov, Sergey Petukhov. (2019). Autonomous Transport Mean Reverse Movement Control by Nodal Points. American Journal of Engineering and Technology Management, 4(5), 73-78. https://doi.org/10.11648/j.ajetm.20190405.11

Copy | Download

ACS Style

Michael Rachkov; Sergey Petukhov. Autonomous Transport Mean Reverse Movement Control by Nodal Points. Am. J. Eng. Technol. Manag. 2019, 4(5), 73-78. doi: 10.11648/j.ajetm.20190405.11

Copy | Download

AMA Style

Michael Rachkov, Sergey Petukhov. Autonomous Transport Mean Reverse Movement Control by Nodal Points. Am J Eng Technol Manag. 2019;4(5):73-78. doi: 10.11648/j.ajetm.20190405.11

Copy | Download

@article{10.11648/j.ajetm.20190405.11,
  author = {Michael Rachkov and Sergey Petukhov},
  title = {Autonomous Transport Mean Reverse Movement Control by Nodal Points},
  journal = {American Journal of Engineering and Technology Management},
  volume = {4},
  number = {5},
  pages = {73-78},
  doi = {10.11648/j.ajetm.20190405.11},
  url = {https://doi.org/10.11648/j.ajetm.20190405.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajetm.20190405.11},
  abstract = {The study presents an exact formulation of control for the reverse moving a transport mean along a polygonal course consisting of rectilinear segments interconnected by nodal points. Appropriateness of the question is caused by the need to figure out a several of tasks: to secure the transport mean in the occasion of а communication crash by returning along the course already passed, to escape rotation in constrained or unsafe conditions, or partial go back for the following avoid of the hurdle and continuation of the forward motion. The control method of forward motion assumes that the route of movement is predetermined, and the path is elaborated by using landmarks. Video cameras are placed on the transport mean for landmark measurement. They are controlled by the operator through the radio channel. Errors in estimating deviation from the supposed course are detected using the multidimensional correlation investigation instrument based on the dynamics of a lateral deviation mistake and a velocity mistake. Reception algorithm of the information is presented on reference points. The outcome of the test showed a considerable preciseness in determining the position vector that provides the reverse movement relative to the reference course with a reasonably admissible mistake while returning to the start spot.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Autonomous Transport Mean Reverse Movement Control by Nodal Points
AU  - Michael Rachkov
AU  - Sergey Petukhov
Y1  - 2019/11/22
PY  - 2019
N1  - https://doi.org/10.11648/j.ajetm.20190405.11
DO  - 10.11648/j.ajetm.20190405.11
T2  - American Journal of Engineering and Technology Management
JF  - American Journal of Engineering and Technology Management
JO  - American Journal of Engineering and Technology Management
SP  - 73
EP  - 78
PB  - Science Publishing Group
SN  - 2575-1441
UR  - https://doi.org/10.11648/j.ajetm.20190405.11
AB  - The study presents an exact formulation of control for the reverse moving a transport mean along a polygonal course consisting of rectilinear segments interconnected by nodal points. Appropriateness of the question is caused by the need to figure out a several of tasks: to secure the transport mean in the occasion of а communication crash by returning along the course already passed, to escape rotation in constrained or unsafe conditions, or partial go back for the following avoid of the hurdle and continuation of the forward motion. The control method of forward motion assumes that the route of movement is predetermined, and the path is elaborated by using landmarks. Video cameras are placed on the transport mean for landmark measurement. They are controlled by the operator through the radio channel. Errors in estimating deviation from the supposed course are detected using the multidimensional correlation investigation instrument based on the dynamics of a lateral deviation mistake and a velocity mistake. Reception algorithm of the information is presented on reference points. The outcome of the test showed a considerable preciseness in determining the position vector that provides the reverse movement relative to the reference course with a reasonably admissible mistake while returning to the start spot.
VL  - 4
IS  - 5
ER  -

Copy | Download

Author Information

Michael Rachkov

Department of Mechanical Engineering, Moscow Polytech, Moscow, Russia
Sergey Petukhov

Department of Mechanical Engineering, Moscow Polytech, Moscow, Russia

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Michael Rachkov, Sergey Petukhov. (2019). Autonomous Transport Mean Reverse Movement Control by Nodal Points. American Journal of Engineering and Technology Management, 4(5), 73-78. https://doi.org/10.11648/j.ajetm.20190405.11

Copy | Download

ACS Style

Michael Rachkov; Sergey Petukhov. Autonomous Transport Mean Reverse Movement Control by Nodal Points. Am. J. Eng. Technol. Manag. 2019, 4(5), 73-78. doi: 10.11648/j.ajetm.20190405.11

Copy | Download

AMA Style

Michael Rachkov, Sergey Petukhov. Autonomous Transport Mean Reverse Movement Control by Nodal Points. Am J Eng Technol Manag. 2019;4(5):73-78. doi: 10.11648/j.ajetm.20190405.11

Copy | Download

@article{10.11648/j.ajetm.20190405.11,
  author = {Michael Rachkov and Sergey Petukhov},
  title = {Autonomous Transport Mean Reverse Movement Control by Nodal Points},
  journal = {American Journal of Engineering and Technology Management},
  volume = {4},
  number = {5},
  pages = {73-78},
  doi = {10.11648/j.ajetm.20190405.11},
  url = {https://doi.org/10.11648/j.ajetm.20190405.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajetm.20190405.11},
  abstract = {The study presents an exact formulation of control for the reverse moving a transport mean along a polygonal course consisting of rectilinear segments interconnected by nodal points. Appropriateness of the question is caused by the need to figure out a several of tasks: to secure the transport mean in the occasion of а communication crash by returning along the course already passed, to escape rotation in constrained or unsafe conditions, or partial go back for the following avoid of the hurdle and continuation of the forward motion. The control method of forward motion assumes that the route of movement is predetermined, and the path is elaborated by using landmarks. Video cameras are placed on the transport mean for landmark measurement. They are controlled by the operator through the radio channel. Errors in estimating deviation from the supposed course are detected using the multidimensional correlation investigation instrument based on the dynamics of a lateral deviation mistake and a velocity mistake. Reception algorithm of the information is presented on reference points. The outcome of the test showed a considerable preciseness in determining the position vector that provides the reverse movement relative to the reference course with a reasonably admissible mistake while returning to the start spot.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Autonomous Transport Mean Reverse Movement Control by Nodal Points
AU  - Michael Rachkov
AU  - Sergey Petukhov
Y1  - 2019/11/22
PY  - 2019
N1  - https://doi.org/10.11648/j.ajetm.20190405.11
DO  - 10.11648/j.ajetm.20190405.11
T2  - American Journal of Engineering and Technology Management
JF  - American Journal of Engineering and Technology Management
JO  - American Journal of Engineering and Technology Management
SP  - 73
EP  - 78
PB  - Science Publishing Group
SN  - 2575-1441
UR  - https://doi.org/10.11648/j.ajetm.20190405.11
AB  - The study presents an exact formulation of control for the reverse moving a transport mean along a polygonal course consisting of rectilinear segments interconnected by nodal points. Appropriateness of the question is caused by the need to figure out a several of tasks: to secure the transport mean in the occasion of а communication crash by returning along the course already passed, to escape rotation in constrained or unsafe conditions, or partial go back for the following avoid of the hurdle and continuation of the forward motion. The control method of forward motion assumes that the route of movement is predetermined, and the path is elaborated by using landmarks. Video cameras are placed on the transport mean for landmark measurement. They are controlled by the operator through the radio channel. Errors in estimating deviation from the supposed course are detected using the multidimensional correlation investigation instrument based on the dynamics of a lateral deviation mistake and a velocity mistake. Reception algorithm of the information is presented on reference points. The outcome of the test showed a considerable preciseness in determining the position vector that provides the reverse movement relative to the reference course with a reasonably admissible mistake while returning to the start spot.
VL  - 4
IS  - 5
ER  -

Copy | Download