Conference Paper2017Cited by 5

Vision based trajectory following robot and swarm

Ishraq Ul Haque, Abul Al Arabi, Shadat Hossain, Tanjina Proma, Nafi Uzzaman, M Ashraful Amin

2017 2nd International Conference on Control and Robotics Engineering (ICCRE)

IEEE, pp. 35–38

  • Sustainable Cities and Communities — Relevance: 67%
DOI: 10.1109/iccre.2017.7935037URL

Abstract

Robots based on vision guidance are very important to the future of vehicle navigation. They have the ability to navigate through a predetermined track and avoid obstacles. They operate remotely with a central computer tracking and guiding them. This allows for communication between robots. This can be used to implement traffic based navigation. Where routes can be recalculated depending on traffic flow. Use of server based system paves the way to collaborate among different robots.

Keywords

  • trajectory tracking
  • multi-robot collaboration
  • swarm robotics
  • Obstacle avoidance
  • telerobotics
  • robot communication

CCDS Authors

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

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Cited By

  1. 1.Sy-Hung Bach, Soo-Yeong Yi. (2022). An Efficient Approach for Line-Following Automated Guided Vehicles Based on Fuzzy Inference Mechanism. Journal of Robotics and Control (JRC), 3(4), 395–401[10.18196/jrc.v3i4.14787]
  2. 2.Ahmed Bendimrad, Ayoub El Amrani, Bouchta El Amrani. (2020). Design and implementation of line follower and obstacle detection robot. International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering, 11(1), 160[10.11591/ijpeds.v11.i1.pp160-168]
  3. 3.Abul Al Arabi, Pranabesh Sarkar, Faysal Ahmed, Waliur Rahman Rafie, Mahfuz Hannan, M Ashraful Amin. (2017). 2D mapping and vertex finding method for path planning in autonomous obstacle avoidance robotic system. , 39–42[10.1109/iccre.2017.7935038]
  4. 4.Adil Hashim, Tanya Saini, Hemant Bhardwaj, Adityan Jothi, Ammannagari Vinay Kumar. (2018). Application of Swarm Intelligence in Autonomous Cars for Obstacle Avoidance. Studies in computational intelligence, 393–404[10.1007/978-981-10-8797-4_41]
  5. 5.Jannatul Nayeem, Mir Oliul Pasha Taj, Md. Shahria Mahmud, Farha Hossain, Abul Al Arabi. (2022). Implementation of Computer Vision in Low Fidelity Robots: Analysis, Challenges, and Design Implications. , 105, 339–344[10.1109/nics56915.2022.10013428]
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