Guidance, Navigation and Control in Robotics, Medical and Aerospace Systems

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The intelligent guidance, navigation and control systems for autonomous systems in robotics, aerospace engineering and medicine are the main focus of this proposal. Increasing requirements for autonomy make systems more and more complex, and, therefore more difficult to control. Recent events have highlighted the utility of the autonomous space and aerial robots for various tasks, including surveillance, space exploration, etc. The main problem with those systems is its ability for accurate localization, positioning and navigation. Space robots are used for outer planet exploration but also for space debris removal from higher orbits. In order to navigate autonomously UAVs or space robots must be able to estimate location and attitude. Position and attitude or pose of the robot is not easy to determine. It may involve, depending of the applications, inertial navigation sensors, GPS, and vision systems. All sensors suffer from number of problems and shortcomings and therefore, advanced sensor/data fusion algorithms are used to estimate position and/or location. This proposal builds on earlier investigation done by the applicant on sensor/data fusion methods and intelligent guidance, navigation and control for robotics. The objective of the proposed research is to make mobile, unmanned systems fully autonomous, and to developed advanced guidance, navigation, and control systems for autonomous vehicles and other moving and dynamic systems based on vision systems. The particular objectives are: 1. To investigate and develop new advanced intelligent methods and algorithms for sensor and data fusion that would allow autonomous systems better perception of its environment; 2. To investigate and develop new advanced guidance, navigation and, control systems and algorithms for unmanned autonomous mobile vehicles and aerospace robots, as well as, other autonomous systems; 3. To develop advanced localization and positioning methods for mobile robots and stationary manipulators that could be used for aerospace, medical and energy applications: 4. To investigate and develop advanced control systems for guidance and positioning of robots with flexible links and joints. The suggested methodology will be based on Adaptive and Extended Kalman Filtering (EKF), as well as, Unscented Kalman Filter (UKF). The adaptive procedure applied to the Kalman Filter gain will be based on fuzzy logic methodology. This would ensure the convergence in the case of signals with coloured noise. This procedure will be compared with some chosen statistical and probabilistic method. In particular, an extended Monte Carlo method and Particle Filter methods will be used. The developed methods, algorithms, and procedures will be applied to aerospace robots, mobile robots and medical manipulators. It is expected that significant progress will be made in robots environment perception and control.