A practical modification of the Hough transform is proposed that improves the detection of low-contrast circular objects. The original circular Hough transform and its numerous modifications are discussed and compared in order to improve both the efficiency and computational complexity of the algorithm. Medical images are selected to verify the algorithm. In particular, the algorithm is applied to localize cell nuclei of cytological smears visualized using a phase contrast microscope.

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In this paper a local trajectory planner is described and applied. This planner works in three dimensional environment populated with static and passive movable obstacles. Dynamics of a moving vehicle and its environment determine the vehicle performance. The performance evaluation is done by minimizing a criterion function. Due to two stage motion planning (decision-trace modes) problem of being trapped by the vehicle in a local minimum of the criterion function is avoided. Environment is perceived at an abstract level therefore the source of environment related data is not very important. The planner, although autonomous, may be adjusted by higher order system (strategic behavior) by changing its parameters. It is not computationally intensive and therefore can be used in real-time applications.

In this paper a Pfaff matrix for doubly generalized N-trailer systems is derived when not only lateral, as in generalized N-trailer systems, but also longitudinal constraints are respected. Based on the matrix, kinematic models are presented for doubly generalized N-trailer systems parameterized with a vector composed of codes of active constraints at each axle. For all constraints active, a closed-form formula for kinematics is derived while for other models-a recursive one is proposed. It is shown how to construct analytically a null space for two types of possible Pfaff matrices and some examples are provided to illustrate introduced formulas. The kinematic models can be used either to test algorithms of motion planning (control) for a broad class of easy parameterizable models or to design or verify wheeled systems.

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