Learning-based Adaptive Compliance Method (LAC)

We propose a novel Learning-based Adaptive Compliance (LAC) algorithm to improve the efficiency and adaptability of symmetric bi-manual manipulation.

Videos

The video intuitively shows the effectiveness of LAC in the dual-arm cooperative handling and the peg-in-hole assembly operations.

Overview

We further made the following contributions:

• We design a novel algorithm framework to complete symmetric bi-manual manipulation based on reinforcement learning. The LAC generates the desired trajectory of dual-arm operations, improving motion planning efficiency. Meanwhile, it adaptively updates impedance parameters to overcome the poor robustness of impedance control.

• We design a centralized Actor-Critic network structure with LSTM networks to achieve cooperative planning and impedance-parameter modification. The centralization of the framework is particularly useful in operations requiring high dual-arm synchronization. Moreover, results demonstrate that the force trend feature captured by LSTM networks significantly impacts the performance of compliance operations.

• Thanks to the efficiency and robustness of LAC, we realize two typical symmetric bi-manual manipulations, the dual-arm cooperative handling operation with random target positions and the peg-in-hole assembly operation in which two arms hold the same peg.

Method

We present the algorithm framework of LAC used in the symmetric bi-manual manipulation. It is a centralized framework consists of two parts. The high-level module is the reinforcement learning running at 20 Hz that provided the object's desired trajectory and the parameters of the impedance controller. The low-level module is the impedance control running at a frequency lower than that of the high-level module. 

Simulation

Environment

The simulation environments of the dual-arm cooperative handling and peg-in-hole assembly are built in Mujoco.

Comparision

The following figures and tables compare the performance of different algorithms in the two practical operations.