CFP last date
20 June 2025
Call for Paper
July Edition
IJCA solicits high quality original research papers for the upcoming July edition of the journal. The last date of research paper submission is 20 June 2025

Submit your paper
Know more
The week's pick
Responsive image
Designing Multi-Tenant E-Learning Systems in the Cloud: A Process-Oriented Approach for Higher Education

Sameh Azouzi Sonia Ayachi Ghannouchi
Random Articles
Reseach Article

Obstacle Avoidance through Sensors in Human Assist Autonomous Robot

by Jagrati Rajput, R.K. Sharma, Kapil Mishra, Pooja Kumari
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 6
Year of Publication: 2025
Authors: Jagrati Rajput, R.K. Sharma, Kapil Mishra, Pooja Kumari
10.5120/ijca2025924939

Jagrati Rajput, R.K. Sharma, Kapil Mishra, Pooja Kumari . Obstacle Avoidance through Sensors in Human Assist Autonomous Robot. International Journal of Computer Applications. 187, 6 ( May 2025), 32-37. DOI=10.5120/ijca2025924939

@article{ 10.5120/ijca2025924939,
author = { Jagrati Rajput, R.K. Sharma, Kapil Mishra, Pooja Kumari },
title = { Obstacle Avoidance through Sensors in Human Assist Autonomous Robot },
journal = { International Journal of Computer Applications },
issue_date = { May 2025 },
volume = { 187 },
number = { 6 },
month = { May },
year = { 2025 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number6/obstacle-avoidance-through-sensors-in-human-assist-autonomous-robot/ },
doi = { 10.5120/ijca2025924939 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-05-29T00:03:07.774940+05:30
%A Jagrati Rajput
%A R.K. Sharma
%A Kapil Mishra
%A Pooja Kumari
%T Obstacle Avoidance through Sensors in Human Assist Autonomous Robot
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 6
%P 32-37
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Anautonomous robot has been designed and developed as a human assistant for real-time situation. The autonomous robot is capable to performing different tasks for a human who is physically challenged and unable to move from one place to another. This robot can detect the avoid the obstacle in its path, the control system of robot uses ultrasonic sensor and image recognition to detect the range of the obstacle. The algorithm for obstacle avoidance used for this robot is described. Since the obstacle detection and avoidancedepends deeply on the range finder algorithm and performance of the sensors which are used in the system. The performance and outcome of the obstacle avoidance algorithm techniques are discussed in detail.

References
  1. Ahn. J.H. , Kwak. S , and Choi. C, “An integrated machine vision system for multiple human Tracking and silhouette extraction”, pp.573-583, IJCA, 2006.
  2. Adam.A, Rivlin.E , and Shimshoni.I , “ Computing the sensory uncertainty field of a Vision-based localization sensor ,” proc . Of the IEEE International Conference on Robotics & Automation, pp. 2993-2999, April 2016.
  3. Awad. F and Shamroukh.R , “Human Detection by Intelligent Machine Urban Search and Rescue Using Image Processing and Neural Networks” International Journal of Intelligent Science , pp.4 39-53, 2014.
  4. Burridge.R and Graham, “Providing machine assistance during extra-vehicular activity”, SPIE, 2001.
  5. Chaturvedi. D.K and Yadav .A “An overview of intelligent moving machine (IMM) IJCA (0975-8887) Vol.128- No.3 Oct 2015.
  6. Eellotto.N and Hu.H, “Vision and laser data fusion for tracking object with a mobile machine”. In proc. IEEE Int. conf. on Machine and Biomimetics (ROBIO), pp. 7-12 China 2016.
  7. Feymer.D and Konolige.K , Tracking object from a mobile platform. In IJCAI-2001 Workshop on Reasoning with Uncertainty in Machine, Seattle, USA, 2011.
  8. Feymer.D and Konolig.K , “Tracking obstacle from a moving platform. Int. Proceeding of 202 int. Symp. On Experimental Machines. pp. 234-244, 2002.
  9. Gold.J and Koren.K, “Obstacle Avoidance with Ultrasonic Sensors”. IEEE Journal of Robotics and Automation, vol. RA-4, No.2, pp. 213-218, 1988.
  10. Hook.A and Koren. K , “Real- time obstacle avoidance for fast moving machine”, IEEE Transactions on system , Man and Cybernetics B , vol.19 no.5 pp. 1179-1187 , 1989.
  11. Hook.A, and Koren. K, “The vector field histogram-fast obstacle avoidance for mobile robots, IEEE Trans. on Robotics and Automation, pp.501-518,2011.
  12. Harrol. J and Latombe .J.C, “Machine motion planning: a distributed representation Approach”, International Journal of Robotics Research, vol.10 no.6, pp. 628-649, 2016.
  13. Jim. N and Mak. K, “Multisensor based human tracking for an indoor service robot”, Submitted to IJRR, 2017.
  14. Jai Bhatia, Ajay Mudgal, and Amita Soni, “Alive Human Detection Using an Autonomous Mobile Rescue Robot”, Department of Electrical & Electronics, PEC University of Technology, Chandigarh, India vol.no.2, July 2015.
  15. Klien. J and Veloso .N, “Depth Camera Based Indoor Mobile Machine Localization and Navigation”, in Proc. of ICRA, pp. 1697-1702, 2012.
  16. Kock.D, Ramesh. V and Meer. P, “Kernel-based object tracking”on Pattern Analysis and Machine Intelligent, vol.25 no.5, pp.564-577, May 2003.
  17. Lyon .G, Treptow. A & Duckett. T, “Quantitative Performance Evaluation of a People Tracking System on a Mobile Robot, Proc. Of ECMR05 (2nd European Conference on Mobile Robots), Ancona, Italy, Sept 2005.
  18. Lamb.H and Wankhade.M, “Human tracking in video surveillance” International Journal of Emerging Technology and Advanced Engineering, ISSN 2250-2459, December 2011.
  19. Mongin.A.K , Chatterji.B.N , Ray A.K . “Design of a real-time tracking system for fast-moving objects IETE J. Res 43, pp.359-369, 2017.
  20. Nick.D and Forsyth.A, “Finding and tracking people from the bottomup”, in Proceeding of Computer Vision and Pattern Recognition (CVPR), Madison Wisconnin , June 2013
  21. Romdhani.S et al.: Computationally Efficient Face Detection, Proceedings of the 8th International Conference on Computer Vision, 2, 2011.
  22. Ryan.J, Zennaro.M, and Howell.A, “An overview of emerging results in cooperative MAV control”, Proc. Of 53rd IEEE Conference on Decision and Control, vol. 1, pp.602-607, 2018.
  23. Spinello.L and Arras.A, “People Detection in RGB-D Data”, in Proc. of IROS Springer, pp.3838-3843, 2014.
  24. Wang L.Tang, T. Ning, H and Hu, W. “Silhouette analysis-based gait recognition for human identification”, IEEE Trans Pattern Anal Mach Intell 25(12): pp.1505-1518, Feb. 2003.
  25. Yadav, A. Gaur, A. Chaturvedi, D, K. “Navigation, Guidance & Control Program for GPS based Autonomous Ground Vehicle”. Materials Today Proceedings Elsevier, Sept 2018
  26. Yadav, A. Gaur, A. Chaturvedi, D, K. Saxena, A, K. Kumar, S. “Development of Navigation, Guidance and Control Program for GPS based Autonomous Ground Vehicle”. Proceeding Intelligent Vehicle.Springer, Sep. 2019.
  27. Yoshimi, T. Nishiyama, M. Sonoura,N. Nakamato ,H.“Development of a Person Following Robot with Vision-based target detection”, Proc. International Robots and Systems, pp.5286-5291, Beijing, China, Oct 2006.
  28. Zhou, H. and Sakane,S. “Sensor planning for mobile robot localization based of probalistic inference using bayesian network,” proc. of the 4th IEEE International Symposium on Assembly and Task Planning, pp. 7-12, May 2001.
Index Terms

Computer Science
Information Sciences

Keywords

Autonomous Robot human assistant system Sensors Obstacle avoidance

Powered by PhDFocusTM