Development of estimation and learning algorithms for embedded systems in mobile robots

Abstract

Mobile robotics is a research area that has been obtaining considerable attention from the scientific community. One of the main challenges in this area is the development of mobile robots that are capable of acting in unknown environments and situations and make the right decisions in order to correctly perform their tasks. The development of these intelligence and autonomous systems consists of a recent, multidisciplinar, and very promising research area that evolves: artificial intelligence, machine learning, estimation theory and others. Another area that has been obtaining great attention by the academic community is the embedded systems area. Opposite as general purpose processors as the ones used in home computers, embedded systems are designed to execute specific tasks with very high efficiency. This research project proposes: (1) the development of learning and state estimation algorithms that will allow mobile robots to act efficiently in unknown and dynamic environments; (2) the integration of mobile robotics and embedded systems through the development of dedicated hardware to execute the equivalent software algorithms.