A robotic system has to understand its environment in order to perform the tasks assigned to it successfully. In such a case, a system capable of learning and decision
making is necessary. In order to achieve this capability, a system must be able to observe its environment with the help of real time data received from its sensors. This paper discusses certain experiments to highlight methods and attributes that can be used for such a learning. These experiments consider attributes recorded in different virtual environments with the
S. Mishra, Radhakrishnan, G., Dr. Deepa Gupta, and Sudarshan, T. S. B., “Acquisition and analysis of robotic data using machine learning techniques”, in Computational Intelligence in Data Mining-Volume 3, Springer India, 2015, pp. 489–498.