Topic Editors

College of Engineering, China Agricultural University, Beijing 100083, China
Dr. Min Xia
Department of Mechanical and Materials Engineering, Western University, London, ON, Canada
Dr. Hui Xie
School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, WA 6102, Australia

Unmanned Vehicles Technology and Embodied Intelligence Systems for Intelligent Transportation

Abstract submission deadline
31 August 2024
Manuscript submission deadline
31 December 2024
Viewed by
205

Topic Information

Dear Colleagues,

At present, the new unmanned vehicles technology and embodied intelligence systems for intelligent transportation are in a period of change. In the foreseeable near future, unmanned systems represented by UGV (Unmanned Ground Vehicle) and UAV (Unmanned Aerial Vehicle) will build new ground and air transportation, logistics, and operation systems, which will have great application potential in various fields of industry and agriculture. Unmanned driving systems (on the open road and the closed road) and intelligent agricultural machinery and equipment are representative intelligent transportation applications. 'Interactive' perception, 'learnable' cognition and decision making, and 'self-growth' behavior control are three important features of embodied intelligence. Correspondingly, multi-sensor (Lidar, millimeter wave radar, and optical sensor) and multi-source information fusion technology, SLAM technology, and bionic vision technology are applied to the perception stage. Brain-imitating intelligence and end-to-end deep learning neural networks are applied to the cognition and decision-making stage. Disturbance self-rejection control, integration control, bionic formation control, and manned/unmanned hybrid cooperative control technology are applied to the behavior control stage.

The scope of solicitation includes, but is not limited to, the following:

  • Automatic driving, intelligent driving, and unmanned driving; embodied intelligence;
  • Perception, cognition, and behavior;
  • SLAM (Simultaneous Localization and Mapping);
  • Lidar, millimeter-wave radar, RGB and RGB-D machine vision perception, and multi-spectral optical perception; 'interactive' perception;
  • 'Learnable' cognition and decision making;
  • 'Self-growth' behavior control; biologically inspired visual perception;
  • Multi-sensor and multi-source information fusion;
  • Brain-imitating intelligence and end-to-end deep learning neural networks;
  • Disturbance observer and active disturbance rejection control;
  • Perception, decision-making and control integration technology;
  • Biologically inspired formation control;
  • Hybrid cooperative control of manned/unmanned systems.

Dr. Jian Chen
Dr. Min Xia
Dr. Hui Xie
Topic Editors

Keywords

  • unmanned systems
  • embodied intelligence
  • agricultural and industrial applications
  • intelligent transport
  • autonomous driving
  • UGV
  • UAV
  • SLAM
  • perception, decision making, and control

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Aerospace
aerospace
2.1 3.4 2014 24 Days CHF 2400 Submit
Applied Sciences
applsci
2.5 5.3 2011 17.8 Days CHF 2400 Submit
Drones
drones
4.4 5.6 2017 21.7 Days CHF 2600 Submit
Electronics
electronics
2.6 5.3 2012 16.8 Days CHF 2400 Submit
Eng
eng
- 2.1 2020 28.3 Days CHF 1200 Submit
Remote Sensing
remotesensing
4.2 8.3 2009 24.7 Days CHF 2700 Submit
Sensors
sensors
3.4 7.3 2001 16.8 Days CHF 2600 Submit

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