We describe and test how information from multiple sources can be combined into a robust visual servoing system. The main objective is integration of visual cues to provide smooth pursuit in a cluttered environment us...
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We describe and test how information from multiple sources can be combined into a robust visual servoing system. The main objective is integration of visual cues to provide smooth pursuit in a cluttered environment using a minimum or no calibration. For that purpose, voting schema and fuzzy logic command fusion are investigated. It is shown that the integration permits detection and rejection of measurement outliers.
In the dynamical systems approach to robot path planning both sensed and remembered information contribute to shape a nonlinear vector field that governs the behavior of an autonomous agent. Such systems perform well ...
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In the dynamical systems approach to robot path planning both sensed and remembered information contribute to shape a nonlinear vector field that governs the behavior of an autonomous agent. Such systems perform well with partial knowledge of the environment and in dynamically changing environments. Nevertheless, it is a local heuristic approach to path planning, and it is not guaranteed to find existing paths. We describe a method of adjusting the spatial resolution of the planner using a dynamical system that operates at a faster time scale than the planning dynamics. This improves the system's ability to utilize both sensed and remembered information, and to solve a larger range of problems without resorting to global path planning.
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