Strategy acquirement by survival robots in outdoor environment

In this research we propose a model of autonomous robot that is able to survive in real world outdoor environment without human intervention. For an autonomous robot, energy is a very important factor, so it is only natural that the ability of the robot to accumulate energy should be used as evaluation of the robot´s survival strategy. The robot in this study is equipped with a solar panel, and a model of neural network ensemble. The solar panel enables the robot to autonomously accumulate energy in the outdoor environment, while the neural network ensemble enables the robot to acquire strategies that are needed in order to survive in the environment. The accumulated energy is considered as the feedback from the environment to measure the efficiency of the strategy exerted by the robot, and used as learning guidance for the robot to survive.