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CS 326 A: Motion Planning http://robotics.stanford.edu/~latombe/cs326/2002 Planning Exploration Strategies
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Exploration Map Building A robot is introduced in a new environment Its task is to build a model (2D or 3D) of this environment It goes from place to place. At each place it acquires a local model that it merges with the current global model
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Example
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Example
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Localization Issue Initial position of the robot reference coordinate frame Dead-reckoning (e.g., odometry) yields increasing errors Need to match each new local model with current global model (correspondence problem)
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Correspondence Problem
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Localization Issue Initial position of the robot reference coordinate frame Dead-reckoning (e.g., odometry) yields increasing errors Need to match each new local model with current global model Simultaneous Localization and Mapping (SLAM) Simultaneous Localization and Mapping (SLAM)
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Loop Issue Courtesy R. Chatila Loops Complex optimization problem (incrementality vs. global optomization)
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Not a New Issue!
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Two Sub-problems in Exploration Where to go next? - Maximize amount of new information - Ensure minimal model overlap - Minimize travel length Next-best view How to best merge the two models? - Minimize expected errors: Kalman filtering, expectation maximization (most likely map)
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Other Exploration Issues Map model: polygonal, occupancy grid, topological network, 3D surfaces, object map, etc… Moving objects “Meaning” of objects Multiple robots Unstructured environments
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Other Exploration Issues Map model: polygonal, occupancy grid, topological network, 3D surfaces, object map, etc… Moving objects “Meaning” of objects Multiple robots Unstructured environments
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