In our work, a robot can proactively ask for help when necessary, based on its awareness of its sensing and actuation limitations. Approaches in which humans provide help to robots do not necessarily reason about the human availability and accuracy. Instead, we model the availability of humans in the robot's environment and present a planning approach that uses such model to generate the robot navigational plans. In particular, we contribute two separate planners that allow a robot to distinguish actions that it cannot complete autonomously from ones that it can. In the first planner, the robot plans autonomous actions when possible and requests help to complete actions that it could not otherwise complete. Then for actions that it can perform autonomously, we use a POMDP policy that incorporates the human availability model to plan actions that reduce uncertainty or that increase the likelihood of the robot finding an available human to help it reduce its uncertainty. We have shown in prior work that asking people in the environment for help during tasks can reduce task completion time and increase the robot's ability to perform tasks.
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