Interval analysis for robot precision evaluation

Abstract

The success of assembly and manipulation tasks is highly dependent on the precision of robotic positioners employed. In turn, precision metrics for robots depend on the kinematic design, choice of actuators, sensors, and control system. In this paper, we investigate the effect of parametric uncertainties on the robot precision using interval analysis. The advantage of interval analysis is that it provides rigorous bounds on the effects of errors in terms of interval numbers. Two types of errors are considered: geometric errors due to link and joint parameter uncertainties, and sensing errors due to inaccurate measurement of joint positions. We show that modeling and simulation of these uncertainties using intervals can provide useful insight into the evaluation of manipulator precision for a given task. In particular, simulation results are offered to predict the required tolerances in a peg-in-hole microassembly operation. It is illustrated that the presented approach can replace computationally more expensive Monte-Carlo simulations to estimate the effect of uncertainties.