Object Localization with Multiple Sensors

We present a method to obtain the position and orientation of an object through measurement from multiple sensors. Raw sensor measurements are subject to limitations of sensor precision and accuracy. Although for most measurements the estimate of position parameters is a linear function of the measurements, the estimate of orientation parameters is a nonlinear function of the measurements. Thus, error in orien tation estimate depends on the distance over which the raw measurements are made. For example, the estimate of the orientation of a line is better, the farther apart two points on the line are. The problem of finding the orientation parame ters is formulated in two steps. The first step computes vec tors from sensor measurements of points. A concept of best features is developed to select an optimal set of all possible vectors. The second step relates the orientation parameters to the vectors from the first step as a linear system. The best estimate is obtained by solving a weighted linear system of the optimal set of vectors in a least squares sense. The opti mal selection of best features improves the estimate substan tially. This method has been implemented for localizing an object in a manipulator end-effector instrumented with cen troid and matrix tactile sensors.