In the last decades, several approaches have been presented to accomplish tasks with a robot or autonomous systems in a glovebox, nevertheless, in nuclear facilities, risky operations are still executed by humans that guarantee a high manipulation capability and dexterity. Inside the gloveboxes, robotic devices have to operate in cluttered environments, or environments with limited space for movement; therefore it is of significant interest to identify grasping poses those are feasible within such constrained environments. In this paper, we present and experimentally evaluate a strategy to synthesize optimal grasps of geometric primitives for anthropomorphic manipulation systems in a constrained environment. The novel strategy has been experimentally evaluated in a cluttered environment (as glovebox mock-up) with realistic objects, as a result, we demonstrate the suitability of our developed algorithm.