Collision Avoidance and Trajectory Planning for Autonomous Mobile Robot: A Spatio-Temporal Deep Learning Approach

K. L. Keung, K. H. Chow, C. K.M. Lee

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

The field of autonomous mobile robots has been gaining significant attention in various industries and research domains. As the future of robotic process automation unfolds, there is an increasing demand for precise robot movement in terms of collision avoidance and trajectory planning. This paper presents a camera-based autonomous mobile robot system that addresses these requirements. The proposed system utilizes a deep learning variational autoencoder with a spatio-temporal model for image analysis processing. This approach enables the system to effectively analyze and understand the visual information. By leveraging deep learning techniques, the system can extract meaningful features and representations from the images, facilitating accurate perception and understanding of the robot's surroundings. This paper contributes to the advancement of autonomous mobile robot systems by proposing a deep learning techniques with reinforcement learning algorithms. The approach offers promising possibilities for enhancing the control and interaction capabilities of mobile robots in real-world scenarios.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1042-1046
Number of pages5
ISBN (Electronic)9798350323153
DOIs
Publication statusPublished - Dec 2023
Event2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 - Singapore, Singapore
Duration: 18 Dec 202321 Dec 2023

Publication series

Name2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023

Conference

Conference2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
Country/TerritorySingapore
CitySingapore
Period18/12/2321/12/23

Keywords

  • Autonomous mobile robots
  • Collision avoidance
  • Spatio-temporal
  • Trajectory planning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Statistics, Probability and Uncertainty
  • Industrial and Manufacturing Engineering
  • Modelling and Simulation
  • Strategy and Management

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