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Intelligent Sensing and Control Technology for Unmanned Vehicles

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 173

Special Issue Editors


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Guest Editor
College of Information Engineering, Henan University of Science and Technology, Luoyang 471000, China
Interests: autonomous collision avoidance of unmanned vehicles
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China
Interests: unmanned surface vehicle; intelligent decision; nonlinear control
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China
Interests: nonlinear control; fault diagnosis; fault tolerant control of unmanned systems

Special Issue Information

Dear Colleagues,

In recent years, intelligent sensing and control technology for unmanned vehicles has driven profound transformations in the transportation field at an unprecedented speed. The core of this technology lies in the integration of various high-precision and high-reliability sensors, such as LiDAR, millimeter wave radar, high-definition cameras, ultrasonic sensors, and inertial navigation units (IMU), which together provide vehicles with a comprehensive perception of the surrounding environment. By integrating and processing these sensor data through advanced algorithms, unmanned vehicles can understand traffic conditions in real time, identify vehicles and other obstacles, and predict their motion trajectories.

In terms of control technology, autonomous driving technology relies on complex control algorithms and artificial intelligence systems to achieve precise control of vehicle acceleration, braking, and steering, ensuring safety and stability during driving. In addition, this technology also integrates advanced functions such as path planning, decision-making, and behavior prediction, enabling vehicles to autonomously navigate to their destinations while strictly adhering to traffic rules and adapting to various complex traffic scenarios.

The unmanned vehicles in this Special Issue include various unmanned carriers in the fields of land, sea, and air, including unmanned ground vehicles, unmanned ships, unmanned aerial vehicles, and so on. The development of intelligent sensing and control technology for unmanned vehicles will greatly enhance the safety and efficiency of the transportation industry and have profound impacts on multiple fields such as infrastructure planning, logistics transportation, and personal travel. With the continuous deepening of research and the increasing maturity of technology, unmanned vehicles are gradually moving from laboratories to practical environments, leading us into a new era of intelligent transportation. This Special Issue, ”Intelligent Sensing and Control Technology for Unmanned Vehicles“, will focus on the latest developments in intelligent sensing and control technology in this field, exploring technological innovation, application challenges, and future development trends, thereby contributing to the further development of unmanned vehicles technology.

Dr. Xiaojie Sun
Dr. Dongdong Mu
Dr. Yue Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

  • unmanned vehicles
  • intelligent sensing
  • sensor fusion
  • motion-planning
  • AI-driven control
  • decision-making
  • behavior prediction
  • collision avoidance
  • safety control
  • autonomous driving

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