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Union Robotics Systems and Automation Laboratory Motion Planning in the Real World Brendan Burns Union College
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Union Robotics Systems and Automation Laboratory Motion Planning Many degrees of freedom Global planning Sampling-based planning “Always on” system Responsive to user requests Productive use of “down” time
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Union Robotics Systems and Automation Laboratory Real World No model of the environment Knowledge from sensors Dynamic obstacles Implications: Uncertainty Sensor feedback
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Union Robotics Systems and Automation Laboratory Sense-Plan-Act Loop Utility-Guided Planning Robot Sensing ? Movement Request Sensor-Directed Request
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Union Robotics Systems and Automation Laboratory Sensing
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Union Robotics Systems and Automation Laboratory Sensing : Voxel Space
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Union Robotics Systems and Automation Laboratory Sensing: Occlusion
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Union Robotics Systems and Automation Laboratory Sensing: Uncertainty
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Union Robotics Systems and Automation Laboratory Example
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Union Robotics Systems and Automation Laboratory Utility-Guided Planning for Uncertain Environments Modified PRM Planning Defer roadmap construction Search using A* Use planning to guide sensing Act when certainty is above threshold
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Union Robotics Systems and Automation Laboratory Example
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Union Robotics Systems and Automation Laboratory Example
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Union Robotics Systems and Automation Laboratory Example
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Union Robotics Systems and Automation Laboratory Example
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Union Robotics Systems and Automation Laboratory Planning perceptions
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Union Robotics Systems and Automation Laboratory Example
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Union Robotics Systems and Automation Laboratory Open Questions/Challenges Integrate sensing while moving Sensor fusion Assess sensor uncertainty Evaluate performance
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