A place-perception experimental platform is proposed on the basis of the prototype based place perception algorithm. In the hardware system, a binocular rig is used as environment perception sensor, and CPU (central processing unit) and GPU (graphic processing unit) coordinated computing unit is used to process multiple tasks, complex logic, intensive data, and so on. The software system is constructed based on Microsoft Robotics Developer Studio platform. Binocular vision service and place perception service are two core services in it. The former is fit for clustered indoor environment, and realizes object recognition and pose estimation simultaneously in wide viewing angle by using RANSAC (RANdom SAmple Consensus), ASIFT (affine scale-invariant feature transform) -GPU and other algorithms. The latter realizes place categorization and region perception and constructs 2D semantic map based on the results of binocular vision and the existing place perception algorithm. The experiments are conducted in a real interior environment in which no artificial label is used. The experiment results show that the robot can robustly perceive open places in its action space online based on the experimental platform, and realizability, effectiveness and practicability of the existing place perception algorithm are verified to a certain extent.