A method for controlling a robot, including the following steps: obtaining first input information associated with a first simulation environment to which a first level of realism is assigned; obtaining second input information associated with a second simulation environment to which a second level of realism is assigned, wherein the first level of realism is different from the second level of realism and each of the first simulation environment and the second simulation environment is based on a robot cell deployment selection and/or a radio connectivity selection; associating the first input information with a first realism value representing the first level of realism wherein the first level of realism indicates a similarity between the first simulation environment and an actual operating environment; associating the second input information with a second realism value representing the second level of realism wherein the second level of realism indicates a similarity between the second simulation environment and the actual operating environment; and modifying, based on the associated first input information and the associated second input information, one or more parameters of a machine learning process used for controlling the robot wherein the first input information and/or the second input information identifies any one or more of the type of an object manipulated by the robot, the shape of the object, the weight of the object, a destination to which the object is to be carried, a moving path along which at least a portion of the robot moved, a speed or a velocity of a movement of the robot, one or more characteristics of the robot, an arrangement of a plurality manipulable objects included in an area, or the number of the plurality of manipulable objects in the area, and the plurality of manipulable objects includes the object. obtaining first input information associated with a first simulation environment to which a first level of realism is assigned; obtaining second input information associated with a second simulation environment to which a second level of realism is assigned, wherein the first level of realism is different from the second level of realism and each of the first simulation environment and the second simulation environment is based on a robot cell deployment selection and/or a radio connectivity selection; associating the first input information with a first realism value representing the first level of realism wherein the first level of realism indicates a similarity between the first simulation environment and an actual operating environment; associating the second input information with a second realism value representing the second level of realism wherein the second level of realism indicates a similarity between the second simulation environment and the actual operating environment; and modifying, based on the associated first input information and the associated second input information, one or more parameters of a machine learning process used for controlling the robot wherein the first input information and/or the second input information identifies any one or more of the type of an object manipulated by the robot, the shape of the object, the weight of the object, a destination to which the object is to be carried, a moving path along which at least a portion of the robot moved, a speed or a velocity of a movement of the robot, one or more characteristics of the robot, an arrangement of a plurality manipulable objects included in an area, or the number of the plurality of manipulable objects in the area, and the plurality of manipulable objects includes the object.