We apply evolutionary algorithm (EA) to the design of controller for adaptive robots. EAs can be successful for more complicated tasks, where traditional engineering methods strugg...
Abstract— Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques w...
Recently, a new approach that involves a form of simulated evolution has been proposed for the building of autonomous robots. However, it is still not clear if this approach may b...
Evidence theory has been widely applied to uncertainty reasoning. In this paper a finite state machine with evidential reasoning is proposed to control autonomous robots. The Khep...
Qingxiang Wu, David A. Bell, Rashid Hafeez Khokhar...
A model-free, biologically-motivated learning and control algorithm called S-learning is described as implemented in an Surveyor SRV-1 mobile robot. S-learning demonstrated learni...
Brandon Rohrer, Michael Bernard, J. Daniel Morrow,...