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Variable impedance control in operation-space is a promising approach tolearning contact-rich manipulation behaviors. One of the main challenges withthis approach is producing a manipulation behavior that ensures the safety ofthe arm and the environment. Such behavior is typically implemented via areward function that penalizes unsafe actions (e.g. obstacle collision, jointlimit extension), but that approach is not always effective and does not resultin behaviors that can be reused in slightly different environments. We show howto combine Riemannian Motion Policies, a class of policies that dynamicallygenerate motion in the presence of safety and collision constraints, withvariable impedance operation-space control to learn safer contact-richmanipulation behaviors.

RMPs for Safe Impedance Control in Contact-Rich Manipulation