An introduction to fuzzy control
An introduction to fuzzy control
Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Principal component neural networks: theory and applications
Principal component neural networks: theory and applications
Slip control and torque optimization using fuzzy logic
Applications of fuzzy logic
Artificial intelligence and mobile robots: case studies of successful robot systems
Artificial intelligence and mobile robots: case studies of successful robot systems
BISMARC: a biologically inspired system for map-based autonomous rover control
Neural Networks - Special issue on neural control and robotics: biology and technology
Fuzzy Logic Techniques for Autonomous Vehicle Navigation
Fuzzy Logic Techniques for Autonomous Vehicle Navigation
Adaptive hierarchy of distributed fuzzy control: application to behavior control of rovers
Adaptive hierarchy of distributed fuzzy control: application to behavior control of rovers
A fuzzy logic controller for an ABS braking system
IEEE Transactions on Fuzzy Systems
Applied soft computing strategies for autonomous field robotics
Autonomous robotic systems
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Operational safety and health monitoring are critical matters for autonomous planetary, rovers operating on remote and challenging terrain. This paper describes rover safety issues and presents an approximate reasoning approach to maintaining vehicle safety in a navigational context. The proposed rover safety module is composed of two distinct behaviors: safe attitude (pitch and roll) management and safe traction management. Fuzzy logic implementations of these behaviors on outdoor terrain are presented. Sensing of vehicle safety coupled with visual neural network-based perception of terrain quality are used to infer safe speeds during rover traversal. In addition, approximate reasoning for self-regulation of internal operating conditions is briefly discussed. The core theoretical foundations of the applied soft computing techniques are presented and supported by descriptions of field tests and laboratory experimental results. For autonomous rovers, the approach provides intrinsic safety cognizance and a capacity for reactive mitigation of navigation risks.