Abstract
It is traditionally difficult to implement fast and accurate position regulation on an industrial robot in the presence of uncertainties. The uncertain factors can be attributed either to the industrial robot itself (e.g., a mismatch of dynamics, mechanical defects such as backlash, etc.) or to the external environment (e.g., calibration errors, misalignment or perturbations of a workpiece, etc.). This paper proposes a systematic approach to implement high-performance position regulation under uncertainties on a general industrial robot (referred to as the main robot) with minimal or no manual teaching. The method is based on a coarse-to-fine strategy that involves configuring an add-on module for the main robot’s end effector. The add-on module consists of a 1000 Hz vision sensor and a high-speed actuator to compensate for accumulated uncertainties. The main robot only focuses on fast and coarse motion, with its trajectories automatically planned by image information from a static low-cost camera. Fast and accurate peg-and-hole alignment in one dimension was implemented as an application scenario by using a commercial parallel-link robot and an add-on compensation module with one degree of freedom (DoF). Experimental results yielded an almost 100% success rate for fast peg-in-hole manipulation (with regulation accuracy at about 0.1 mm) when the workpiece was randomly placed.
Highlights
Position regulation with respect to objects of interest in terms of set-point positioning or trajectory tracking is a fundamental function of an industrial robot
For robots deployed in the manufacturing industry, position regulation at a fast speed and satisfactory accuracy leads to high productivity, and the ability to adapt to many uncertainties leads to task flexibility and efficiency that eventually helps reduce cost
Based on the dynamic compensation approach [10], we propose a systematic approach for high-performance position regulation under uncertainty
Summary
Position regulation with respect to objects of interest in terms of set-point positioning or trajectory tracking is a fundamental function of an industrial robot. The method features a user-friendly interface developed by commercial robot manufacturers, and is applicable to various tasks that require no knowledge on the part of the user of the mapping between the user-concerned task space and the actuation-concerned joint space. It is usually motion optimized and reliable so long as task conditions do not change. As detailed in [1], negative effects of nonlinear dynamics during high-speed motion may be pre-compensated in order to achieve accurate path tracking during the playback phase. It is impossible for a Sensors 2016, 16, 1195; doi:10.3390/s16081195 www.mdpi.com/journal/sensors
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