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Paper ThCT13.1

Yu, Jingjin (Rutgers University), Aslam, Javed (Northeastern University), Karaman, Sertac (Massachusetts Institute of Technology), Rus, Daniela (MIT)

Anytime Planning of Optimal Schedules for a Mobile Sensing Robot

Scheduled for presentation during the Regular session "Planning, Scheduling and Coordination" (ThCT13), Thursday, October 1, 2015, 11:20−11:35, Saal 8

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 20, 2019

Keywords Planning, Scheduling and Coordination, Sensor-based Planning, Optimal Control

Abstract

We study the problem in which a mobile sensing robot is tasked to travel among and gather intelligence at a set of spatially distributed point-of-interests (POIs). The quality of the information collected at each POI is characterized by some sensory (reward) function of time. With limited fuel, the robot must balance between spending time traveling to more POIs and performing time-consuming sensing activities at the visited POIs to maximize the overall reward. In a dual formulation, the robot may be required to acquire a minimum mount of reward with the least amount of time. We propose an anytime planning algorithm for solving these two NP-hard problems to arbitrary precision for arbitrary reward functions. The algorithm is effective on large instances with tens to hundreds of POIs, as demonstrated with an extensive set of computational experiments. Besides mobile sensor scheduling, our algorithm also applies to automation scenarios such as intelligent and optimal itinerary planning.

 

 

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