Union Robotics Systems and Automation Laboratory

Motion Planning in the Real World

Brendan BurnsUnion College

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

Union Robotics Systems and Automation Laboratory

Real World

No model of the environment Knowledge from sensors Dynamic obstacles

Implications: Uncertainty Sensor feedback

Union Robotics Systems and Automation Laboratory

Sense-Plan-Act Loop

Utility-GuidedPlanning Robot

Sensing

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MovementRequest

Sensor-DirectedRequest

Union Robotics Systems and Automation Laboratory

Sensing

Union Robotics Systems and Automation Laboratory

Sensing : Voxel Space

Union Robotics Systems and Automation Laboratory

Sensing: Occlusion

Union Robotics Systems and Automation Laboratory

Sensing: Uncertainty

Union Robotics Systems and Automation Laboratory

Example

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

Union Robotics Systems and Automation Laboratory

Example

Union Robotics Systems and Automation Laboratory

Example

Union Robotics Systems and Automation Laboratory

Example

Union Robotics Systems and Automation Laboratory

Example

Union Robotics Systems and Automation Laboratory

Planning perceptions

Union Robotics Systems and Automation Laboratory

Example

Union Robotics Systems and Automation Laboratory

Open Questions/Challenges

Integrate sensing while moving Sensor fusion Assess sensor uncertainty Evaluate performance