Increasing endurance of an autonomous robot using an Immune-Inspired framework
Maizura Mokhtar, Joe Howe
- Year
- 2011
- Citations
- 3
Abstract
This paper describes the implementation of an online immune-inspired framework to help increase endurance of an autonomous robot. Endurance is defined as the ability of the robot to exert itself for a long period of time. The immune-inspired framework provides such capability by monitoring the behavior of the robot to ensure continuous and safe behavior. The immune-inspired framework combines innate and adaptive immune inspired algorithms. Innate uses a dendritic cell based innate immune algorithm, and adaptive uses an instance based B-cell approach. Results presented in this paper shows that when the robot is implemented with the immune-inspired framework, health and survivability of a robot is improved, therefore increasing its endurance.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991