Real-time velocity scaling and obstacle avoidance for industrial robots using fuzzy dynamic movement primitives and virtual impedances

This paper aims to increase the safety of the robots’ operation by developing a novel method for real-time implementation of velocity scaling and obstacle avoidance as the two widely accepted safety increasing concepts.

A fuzzy version of dynamic movement primitive (DMP) framework is proposed as a real-time trajectory generator with imbedded velocity scaling capability. Time constant of the DMP system is determined by a fuzzy system which makes decisions based on the distance from obstacle to the robot’s workspace and its velocity projection toward the workspace. Moreover, a combination of the DMP framework with a human-like steering mechanism and a novel configuration of virtual impedances is proposed for real-time obstacle avoidance.

The results confirm the effectiveness of the proposed method in real-time implementation of the velocity scaling and obstacle avoidance concepts in different cases of single and multiple stationary obstacles as well as moving obstacles.

As the provided experiments indicate, the proposed method can effectively increase the real-time safety of the robots’ operations. This is achieved by developing a simple method with low computational loads.

This paper proposes a novel method for real-time implementation of velocity scaling and obstacle avoidance concepts. This method eliminates the need for modification of original DMP formulation. The velocity scaling concept is implemented by using a fuzzy system to adjust the DMP’s time constant. Furthermore, the novel impedance configuration makes it possible to obtain a non-oscillatory convergence to the desired path, in all degrees of freedom.