Transferability-based Chain Motion Mapping from Humans to Humanoids for Teleoperation

TL;DR

This paper introduces a transferability-based approach for mapping human motions to humanoid robots, reducing the need for pair-specific training by leveraging existing mappings and a novel synergy extraction method.

Contribution

It proposes the SyDa autoencoder-based synergy mapping and a transferability metric to efficiently form mapping chains for new human-robot pairs, enhancing generalization and accuracy.

Findings

SyDa improves mapping accuracy and generalizability.

SyDa enables bidirectional motion mapping without direction bias.

The transferability metric predicts pair compatibility for teleoperation.

Abstract

Although data-driven motion mapping methods are promising to allow intuitive robot control and teleoperation that generate human-like robot movement, they normally require tedious pair-wise training for each specific human and robot pair. This paper proposes a transferability-based mapping scheme to allow new robot and human input systems to leverage the mapping of existing trained pairs to form a mapping transfer chain, which will reduce the number of new pair-specific mappings that need to be generated. The first part of the mapping schematic is the development of a Synergy Mapping via Dual-Autoencoder (SyDa) method. This method uses the latent features from two autoencoders to extract the common synergy of the two agents. Secondly, a transferability metric is created that approximates how well the mapping between a pair of agents will perform compared to another pair before creating the motion mapping models. Thus, it can guide the formation of an optimal mapping chain for the new human-robot pair. Experiments with human subjects and a Pepper robot demonstrated 1) The SyDa method improves the accuracy and generalizability of the pair mappings, 2) the SyDa method allows for bidirectional mapping that does not prioritize the direction of mapping motion, and 3) the transferability metric measures how compatible two agents are for accurate teleoperation. The combination of the SyDa method and transferability metric creates generalizable and accurate mapping need to create the transfer mapping chain.