Extrinsic Calibration of a Vision Mounted Sensor on a Robot

A vision sensor is mounted on a robot to detect surrounding objects. Its mounting position and orientation must be identified, resulting in an extrinsic calibration problem. This paper presents three classes of extrinsic calibration procedures. All use closed-form solutions. The class A calibration procedure requires a reference object at a precalibrated location. The class B calibration procedure takes advantage of a robot's mobility. It requires a reference frame but not precalibration. The class C procedure, by taking full advantage of both robot mobility and dexterity, requires no reference object but the simplest one-a visible point. In simulation studies, the class A, B, and C calibration procedures have produced estimates successfully converging to true extrinsic parameter values. Except the class A calibration procedure, which yields biased results unless the precalibration is free from errors, field experiments have been carried out for class B and C calibration procedures. For comparison, two existing B-type calibration methods, namely, those of Tsai and Lenz and Shiu and Ahmad, have also been tested with real data. Individually, each method has achieved consistent results. Collectively, their results appear to be comparable. Standard deviations obtained by class B and the Tsai-Lenz methods have been smaller than those of the Shiu-Ahmad method. On average, the Tsai-Lenz method has achieved the smallest standard deviations.