This paper analyzes a new strategy for motion generation in human–robot co-manipulation. The benefit of this strategy is to promote transparent co-manipulation that preserves the professional skill gestures while assisting the user. Newton’s second law is used to compute and plan the trajectory based on the force and moment applied by the user on the robot end-effector. Thus, the trajectory followed by the robot at the point of interaction is similar to that of an object manipulated by hand in daily life, giving a feeling of free object manipulation. Moreover, the setting of the model parameters is intuitive, as they represent physical characteristics. We compare this co-manipulation strategy with the classical stiffness method through simulations and experiments. The results obtained show that the trajectory generated by our virtual solid method reduces the manipulation forces and enhances transparency.
Moutsinga et al. (Tue,) studied this question.