Active sensing data collection with autonomous mobile robots

With the introduction of autonomous robots that help perform various tasks in our environments, we can opportunistically use them for collecting fine-grain sensor measurements about our surroundings. Use of mobile robots for data collection scales much better than static sensors in terms of number of measurement locations and provide more fine-grain accuracy and reliability than alternate human crowd-sourcing efforts. One of the unique features of mobile robots is the ability to control and direct where and when measurements should be collected. In this paper, we present a system to compute paths for the robot to follow that incorporates the robot's limited expected deployment time, expected measurement value at each location, and a history of when each location was last visited.