Moving Object Detection and Control Using Remote Sensing and Artificial Intelligence II
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".
Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 3070
Special Issue Editors
Interests: control engineering; optimization; differential games; artificial intelligence; sensitivity of control; remote sensing; technology development; applications
Special Issues, Collections and Topics in MDPI journals
Interests: engineering; computer science; automation and control systems; transportation; robotics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Moving objects constitute a significant part of all technical objects, for which the method of controlling their movement significantly affects both operating costs and the accuracy as well as safety of transport tasks. This applies to land, sea, and air objects in terms of manned and unmanned facilities. Remote sensing devices, such as radar, lidar, and other highly specialized measurement solutions, are used in the detection as well as control of moving objects. When planning and implementing the motion control of objects, there are many possible acceptable solutions from which the best or optimal solution should be selected. To find it, both static and dynamic optimization deterministic methods, in addition to heuristic methods of particle swarms, are used, as are very effective methods of artificial intelligence in the form of evolutionary algorithms and neuro-fuzzy regulators. The topics of interest also include other AI approaches applied for the detection, path planning, and motion control of various moving objects, such as autonomous vehicles, self-driving cars, aircrafts, and ships, based on machine learning, neural networks as well as deep learning, fuzzy logic, and multiagent as well as expert systems.
In addition, moving objects are often affected by various types of interference, which are compensated for via adaptive algorithms using the following methods: self-tuning, a model reference system, or gain scheduling.
When carrying out transport tasks, there are situations of passing by many other objects. In such situations, the subjectivity of the operator of an object in assessing the navigational situation is important. They must take into account the applicable legal rules in addition to the possibility of making a mistake and contributing to a collision situation, which can be considered as a conflict situation. Game theory, which is a branch of modern mathematics, including the theory of conflict situations and the construction as well as analysis of their models, comes to the rescue. Therefore, it is appropriate to treat the process of passing objects safely as a game, taking into account the cooperation or non-cooperation between objects.
For this Special Issue, we seek innovative approaches that use remote sensing and control to develop appropriate algorithms of computer-aided maneuvering decisions, calculating all possible solutions of the task and proposing one of the best ones.
We welcome review papers, case studies, computer simulations, technology developments, and applications.
You may choose our Joint Special Issue in Remote Sensing.
Prof. Dr. Józef Lisowski
Dr. Agnieszka Lazarowska
Guest Editors
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Keywords
- land, sea, and aerial moving objects
- manned and unmanned objects
- remote sensing
- artificial intelligence
- control engineering
- multicriteria optimization
- adaptive control
- game theory application
- sensitivity of control
- machine learning
- neural networks and deep learning
- fuzzy logic
- multiagent systems
- expert systems
- autonomous vehicles
- swarm intelligence
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