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Given a mapped environment, we formulate the problem of visually tracking andfollowing an evader using a probabilistic framework. In this work, we considera non-holonomic robot with a limited visibility depth sensor in an indoorenvironment with obstacles. The mobile robot that follows the target isconsidered a pursuer and the agent being followed is considered an evader. Wepropose a probabilistic framework for both the pursuer and evader to achievetheir conflicting goals. We introduce a smart evader that has information aboutthe location of the pursuer. The goal of this variant of the evader is to avoidbeing tracked by the pursuer by using the visibility region informationobtained from the pursuer, to further challenge the proposed smart pursuer. Tovalidate the efficiency of the framework, we conduct several experiments insimulation by using Gazebo and evaluate the success rate of tracking an evaderin various environments with different pursuer to evader speed ratios. Throughour experiments we validate our hypothesis that a smart pursuer tracks anevader more effectively than a pursuer that just navigates in the environmentrandomly. We also validate that an evader that is aware of the actions of thepursuer is more successful at avoiding getting tracked by a smart pursuer thana random evader. Finally, we empirically show that while a smart pursuer doesincrease it's average success rate of tracking compared to a random pursuer,there is an increased variance in its success rate distribution when the evaderbecomes aware of its actions.

Active Adversarial Evader Tracking with a Probabilistic Pursuer under the Pursuit-Evasion Game Framework