Abstract
In this paper, a new comprehensive dynamic friction model for a collaborative industrial robot joint that considers the velocity, temperature, and load torque is proposed. The variation of load-dependent friction among the four-quadrant operation depending on the sign of load-torque and speed is studied. The new model’s passivity property is analyzed to obtain a physically meaningful and experimentally identified friction model. A sufficient condition is presented in terms of a simple algebraic inequality involving the parameters of the model. The model parameter identification procedure and validation of model effectiveness are demonstrated experimentally on a commercial collaborative robot manipulator. Moreover, the proposed friction model’s benefits are demonstrated in two different robot applications: friction compensation and direct teaching (smooth lead-through programming) applications. Significant tracking performance improvement in the root-mean-square errors up to 76% was achieved with the proposed friction model compared to the uncompensated cases in the friction compensation application. In the direct teaching application, the new model, which precisely estimates joint friction, results in a significant decrease in interaction forces up to 66%. These experimental results validate the performance of the proposed friction model.
Highlights
Actuation systems in collaborative robots rely on geared drive systems to obtain the relatively low-speed but high-torque mechanical output
We extended the generic form of a dynamic friction model τ f that takes into account internal state z, velocity, load, quadrant, and temperature-dependent effects, i.e.. for each joint τf,i = δ(zi) + ζ, i = 1, · · ·, NDOF . (5)
This paper aims to develop the extended-term ζ (q, T, τL ) so that the comprehensive friction model describes the robot joint friction phenomena accurately
Summary
Actuation systems in collaborative robots rely on geared drive systems to obtain the relatively low-speed but high-torque mechanical output. Friction is one of the unavoidable side-effects of using a geared drive actuation system. The associate editor coordinating the review of this manuscript and approving it for publication was Yangmin Li. the performance of collaborative industrial robots. This is for tracking applications, and for more advanced applications like estimation of contact forces for sensorless force control [6]–[8], sensitive collision detection [9], and force/torque sensorless direct teaching control [10]. Since the compensation technique is typically model-based, the knowledge of a suitable friction model that predicts the real friction is required. In general, friction model uncertainties and variations reduce the estimation reliability
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