Current methods for off-road navigation using vehicle and terrain models to predict future vehicle response are limited by the accuracy of the models they use and can suffer if the world is unknown or if conditions change and the models become inaccurate. In this paper, an adaptive approach is presented that closes the loop around the vehicle predictions. This approach is applied to an autonomous vehicle known as field robots used in agriculture.

Agricultural Robotics is the logical proliferation of automation technology into bio-systems such as agriculture, forestry, green house, horticulture etc. Presently a number of researches are being done to increase their applications. Some of the scientist contributions are mobile robot, flying robot, forester robot, Demeter which are exclusively used for agriculture. A brief discussion is being done about the types of robots which increase the accuracy and precision of the agriculture. 

Experiments are being done on newly proposed world’s smallest, weightless robot for using them as scouts in fields. Even in developing countries, such as India and Brazil, farmers are interested in using robots to tend fields of crops, pick fruit, or even maintain animal. At present time, agriculture robots must have human interaction in order to compensate for programming complexity issues.