Task-oriented Motion Mapping on Robots of Various Configuration using Body Role Division

by   Kazuhiro Sasabuchi, et al.

Many works in robot teaching either focus on teaching a high-level abstract knowledge such as task constraints, or low-level concrete knowledge such as the motion for accomplishing a task. However, we show that both high-level and low-level knowledge is required for teaching a complex task sequence such as opening and holding a fridge with one arm while reaching inside with the other. In this paper, we propose a body role division approach, which maps both high-level task goals and low-level motion obtained through human demonstration, to robots of various configurations. The method is inspired by facts on human body motion, and uses a body structural analogy to decompose a robot's body configuration into different roles: body parts that are dominant for achieving a demonstrated motion, and body parts that are substitutional for adjusting the motion to achieve an instructed task goal. Our results show that our method scales to robots of different number of arm links, and that both high and low level knowledge is mapped to achieve a multi-step dual arm manipulation task. In addition, our results indicate that when either the high or low level knowledge of the task is missing, or when mapping is done without the role division, a robot fails to open a fridge door or is not able to navigate its footprint appropriately for an upcoming task. We show that such results not only apply to human-shaped robots with two link arms, but to robots with less degrees of freedom such as a one link armed robot.



There are no comments yet.


page 1

page 4

page 5

page 7


A Learning-from-Observation Framework: One-Shot Robot Teaching for Grasp-Manipulation-Release Household Operations

A household robot is expected to perform various manipulative operations...

MaestROB: A Robotics Framework for Integrated Orchestration of Low-Level Control and High-Level Reasoning

This paper describes a framework called MaestROB. It is designed to make...

Hierarchical Optimization for Whole-Body Control of Wheeled Inverted Pendulum Humanoids

In this paper, we present a whole-body control framework for Wheeled Inv...

A Transferable Legged Mobile Manipulation Framework Based on Disturbance Predictive Control

Due to their ability to adapt to different terrains, quadruped robots ha...

Design and Workspace Characterisation of Malleable Robots

For the majority of tasks performed by traditional serial robot arms, su...

A Comparison Between Joint Space and Task Space Mappings for Dynamic Teleoperation of an Anthropomorphic Robotic Arm in Reaction Tests

Teleoperation (i.e., controlling a robot with human motion) proves promi...

Towards Robotic Laboratory Automation Plug Play: Teaching-free Robot Integration with the LAPP Digital Twin

The Laboratory Automation Plug Play (LAPP) framework is a high-level...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.