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Subjective Trusts for the Control of Mobile Robots under Uncertainty
Eugene Kagan1, Alexander Rybalov2
1Department Industrial Engineering, Ariel University, Ariel 4076414, Israel.
Entropy (Basel, Switzerland)
|June 24, 2022
Summary
This study introduces novel multi-valued logic for mobile robot control under uncertainty. It enables autonomous decision-making using subjective trusts and artificial neural networks for robot swarming.
Area of Science:
- Robotics
- Artificial Intelligence
- Control Theory
Background:
- Mobile robots often operate with imperfect information and uncertainty.
- Existing control methods may rely on externally defined probabilities, which are not always available.
Purpose of the Study:
- To develop methods for handling imperfect information in autonomous mobile robot control.
- To introduce a novel control technique for robots operating under uncertainty without relying on external probabilities.
Main Methods:
- Utilizing novel multi-valued logic techniques based on subjective trust measures.
- Applying artificial neural networks with mobile neurons for robot swarming.
- Employing internal control mechanisms without external probability references.
Main Results:
- Demonstrated effective handling of non-probabilistic uncertainties.
- Successfully specified robot movements and enabled direct definition of robot swarming.
- Verified proposed methods through numerical simulations and practical examples.
Conclusions:
- The developed framework provides a basis for processing non-probabilistic uncertainties.
- Enables individual decision-making for mobile robots with imperfect information.
- Offers a new approach to autonomous robot control and collective behavior.
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