Theoretical and experimental contributions in the field of orientation and navigation for intelligent systems

Keywords: sensors, obstacle avoidance algorithm, navigation, orientation, autonomous.

At the international and national level, studies are being carried out on the issue of controlling robots with specific assistance to people with disabilities, developing solutions that are as efficient as possible and closer to human behavior. Implementations of features that closely mimic certain human behaviors have been implemented: grip, voice recognition, visual recognition; All this gives people with disabilities a certain degree of freedom and comfort. An important emphasis is also put on the implementation of local and remote management applications and solutions for dedicated systems for telepresence systems.

Starting from these ideas, the research carried out within the present Ph.D. thesis focused on the development of an intelligent system able to guide itself autonomously and to be able to follow the imposed trajectories as well as the calculation of new trajectories, avoiding the possible obstacles or other limitations along on the way.

The main objectives of the doctoral thesis are as follows:
– Integration of sensors (for inertial navigation and obstacle detection) available on the consumer market at a low price, obtaining results with minimal errors, using error elimination algorithms.
– The study and implementation of data fusion algorithms provided by inertial navigation sensors that are available at the lowest prices.
– Study and optimization of some obstacle detection and avoidance algorithms using 8-bit microcontroller computing systems.
– Implementation of a simulator to verify obstacle avoidance algorithms, autonomous guidance and navigation algorithms for intelligent systems.