We introduce and study the problem in which a mobile sensing robot (ourtourist) is tasked to travel among and gather intelligence at a set ofspatially distributed point-of-interests (POIs). The quality of the informationcollected at each POI is characterized by some non-decreasing reward functionover the time spent at the POI. With limited time budget, the robot mustbalance between spending time traveling to POIs and spending time at POIs forinformation collection (sensing) so as to maximize the total reward.Alternatively, the robot may be required to acquire a minimum mount of rewardand hopes to do so with the least amount of time. We propose a mixed integerprogramming (MIP) based anytime algorithm for solving these two NP-hardoptimization problems to arbitrary precision. The effectiveness of ouralgorithm is demonstrated using an extensive set of computational experimentsincluding the planning of a realistic itinerary for a first-time tourist inIstanbul.
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