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Varying terrain conditions and limited field-of-view restricts the visibilityof aerial robots while performing visual monitoring operations. In this paper,we study the multi-point monitoring problem on a 2.5D terrain using an unmannedaerial vehicle (UAV) with limited camera field-of-view. This problem is NP-Hardand hence we develop a two phase strategy to compute an approximate tour forthe UAV. In the first phase, visibility regions on the flight plane aredetermined for each point of interest. In the second phase, a tour for the UAVto visit each visibility region is computed by casting the problem as aninstance of the Traveling Salesman Problem with Neighbourhoods (TSPN). Wedesign a constant-factor approximation algorithm for the TSPN instance.Further, we reduce the TSPN instance to an instance of the GeneralizedTraveling Salesman Problem (GTSP) and devise an ILP formulation to solve it. Wepresent a comparative evaluation of solutions computed using a branch-and-cutimplementation and an off-the-shelf GTSP tool -- GLNS, while varying the pointsof interest density, sampling resolution and camera field-of-view. We also showresults from preliminary field experiments.

Visual Monitoring for Multiple Points of Interest on a 2.5D Terrain using a UAV with Limited Field-of-View Constraint