Collision Preventing Phase-Progress Control for Velocity Adaptation in Human-Robot Collaboration

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00336417" target="_blank" >RIV/68407700:21230/19:00336417 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/Humanoids43949.2019.9035065" target="_blank" >https://doi.org/10.1109/Humanoids43949.2019.9035065</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/Humanoids43949.2019.9035065" target="_blank" >10.1109/Humanoids43949.2019.9035065</a>

Result language

angličtina

Original language name

Collision Preventing Phase-Progress Control for Velocity Adaptation in Human-Robot Collaboration

Original language description

As robots are leaving dedicated areas on the factory floor and start to share workspaces with humans, safety of such collaboration becomes a major challenge. In this work, we propose new approaches to robot velocity modulation: while the robot is on a path prescribed by the task, it predicts possible collisions with the human and gradually slows down, proportionally to the danger of collision. Two principal approaches are developed—Impulse Orb and Prognosis Window—that dynamically determine the possible robot-induced collisions and apply a novel velocity modulating approach, in which the phase progress of the robot trajectory is modulated while the desired robot path remains intact. The methods guarantee that the robot will halt before contacting the human, but they are less conservative and more flexible than solutions using reduced speed and complete stop only, thereby increasing the effectiveness of human-robot collaboration. This approach is especially useful in constrained setups where the robot path is prescribed. Speed modulation is smooth and does not lead to abrupt motions, making the behavior of the robot also better understandable for the human counterpart. The two principal methods under different parameter settings are experimentally validated in a human-robot interaction scenario with the Franka Emika Panda robot, an external RGB-D camera, and human keypoint detection using OpenPose.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

20204 - Robotics and automatic control

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)

ISBN

978-1-5386-7629-5

ISSN

2164-0572

e-ISSN

2164-0580

Number of pages

8

Pages from-to

266-273

Publisher name

IEEE

Place of publication

Piscataway, NJ

Event location

Toronto

Event date

Oct 15, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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