The absolute accuracy of a robot depends to a large extent on the accuracy with which its kinematic parameters are known. Many methods have been explored for inferring the kinematic parameters of a robot from measurements taken as it moves. Some require an external global positioning system, usually optical or sonic. We have used instead a simple radial-distance linear transducer (LVDT) which measures the distance from a fixed point in the workspace to the robot's endpoint. This scalar data is accumulated as the robot endpoint is moved within one or more spherical "shells" centered about the fixed point. Optimal values for all of the independent kinematic parameters of the robot can then be found. Here we discuss the motivation, theory, implementation, and performance of this particularly easy calibration and parameter identification method. We also address a recent disagreement in the literature about the class of measurements needed to fully identify a robot's kinematic parameters.