Learning Variable Impedance Skills from Demonstrations with Passivity Guarantee
This work addresses the need for adaptive robot control in dynamic environments like households, though it appears incremental as it builds on existing learning-from-demonstration and variable impedance control techniques.
The paper tackles the problem of enabling robots to perform variable impedance control for manipulation tasks by learning from human demonstrations, resulting in a framework that estimates stiffness matrices and uses a novel tank-based control approach to ensure passivity, with evaluations showing superior robustness and easier implementation compared to traditional methods.
Robots are increasingly being deployed not only in workplaces but also in households. Effectively execute of manipulation tasks by robots relies on variable impedance control with contact forces. Furthermore, robots should possess adaptive capabilities to handle the considerable variations exhibited by different robotic tasks in dynamic environments, which can be obtained through human demonstrations. This paper presents a learning-from-demonstration framework that integrates force sensing and motion information to facilitate variable impedance control. The proposed approach involves the estimation of full stiffness matrices from human demonstrations, which are then combined with sensed forces and motion information to create a model using the non-parametric method. This model allows the robot to replicate the demonstrated task while also responding appropriately to new task conditions through the use of the state-dependent stiffness profile. Additionally, a novel tank based variable impedance control approach is proposed to ensure passivity by using the learned stiffness. The proposed approach was evaluated using two virtual variable stiffness systems. The first evaluation demonstrates that the stiffness estimated approach exhibits superior robustness compared to traditional methods when tested on manual datasets, and the second evaluation illustrates that the novel tank based approach is more easily implementable compared to traditional variable impedance control approaches.