We present a robust target tracking algorithm for amobilerobot.Itisassumedthatamobilerobotcarriesasensor with a fan-shaped field of view and finite sensing range. The goal of the proposed tracking algorithm is to minimize the probability of losing a target. If the distribution of the next position of a moving target is available as a Gaussian distributionfromamotionpredictionalgorithm,theproposed algorithm can guarantee the tracking success probability. In addition, the proposed method minimizes the moving distance of the mobile robot based on the chosen bound on the trackingsuccessprobability.Whiletheconsideredproblemis anon-convexoptimizationproblem,wederiveaclosed-form solution when the heading is fixed and develop a real-time algorithm for solving the considered target tracking problem. We also present a robust target tracking algorithm for aerialrobotsin3D.Theperformanceoftheproposedmethod is evaluated extensively in simulation. The proposed algorithm has been successful applied in field experiments using PioneermobilerobotwithaMicrosoftKinectsensorforfollowing a pedestrian.

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• Chance-constrained target tracking using sensors with bounded fan-shaped sensing regions