This paper considers experimental investigation of an antagonistically actuated robot manipulator. The focus of the investigation is how biarticular actuation contributes to control of the manipulator. Based on the feature that antagonistically robot manipulators can be controlled by feedforward control with constant inputs, this paper treats the case of PTP (point-to-point) control of robot postures. Due to expectation of difficulty for analytical approach, this paper takes experimental methodology of acquiring mappings between sensory and motor spaces by ANNs (artificial neural networks). Based on the idea that contribution of biarticular actuation may be influenced by choice of a sensory space, this paper considers not only joint angles of a manipulator but also Cartesian coordinate and angles in binocular visual space at the hand of the manipulator as sensory spaces. For each of them, the mappings obtained from trained ANNs are compared for the cases with and without biarticular actuation, based on interpolation performance of the ANNs examined through PTP control of the manipulator. The results of the comparison shows that choice of a sensory space is less effective to the interpolation performance in the case of biarticular actuation.