Sensor-based Navigation and Integrated Control of Ambient Intelligent Wheeled Robots with Tire-Ground Interaction Uncertainties

This paper regards the synthesis of intelligent non-visual sensor-based navigation, motion planning and the integrated control of indoor ambient adaptive wheel-based mobile robots in unknown environments with tire-ground interaction uncertainties. The problem relates to searching appropriate techniques how to navigate towards a target position in an unknown environment when the obstacles to avoid are discovered in real time, and how to maintain collision free motion of a high dynamic performance. Environments characterized by variable ground surface conditions with immobile obstacles of different shapes and sizes will be considered in the paper as unexpected disturbances, i.e. system uncertainties. The tools developed to address this issue thus consist of the combination of cognitive motion planning and control theory techniques, including a nonlinear model-based approach. Two characteristic approaches to integrated control are evaluated in the paper: a kinematical as well as dynamic one, in the sense of control efficiency and robustness to the environmental and model uncertainties. Characteristic simulation tests are performed to verify the proposed algorithms.