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This paper presents a method of path planning for a mobile robot with a pan-tilt camera to find target objects under object-pose uncertainties caused by environmental changes or map inaccuracy. The uncertainties of object poses are represented by probability distributions on both a geometric map and a grid map. Based on these maps, the proposed method generates a weighted Voronoi graph, and plans a path with a short travel time, high passability, and high visibility of the target objects. The total path is the concatenation of paths to reach a goal and paths to observe a target object. The paper proposes a two-layered planning scheme, in which the candidate paths between subgoals are planned on the lower layer, and they are integrated on the upper layer.