Online Foot-Strike Detection Using Inertial Measurements for Multi-Legged Walking Robots

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00328380" target="_blank" >RIV/68407700:21230/18:00328380 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8594010" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8594010</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS.2018.8594010" target="_blank" >10.1109/IROS.2018.8594010</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Online Foot-Strike Detection Using Inertial Measurements for Multi-Legged Walking Robots

Popis výsledku v původním jazyce

Proprioceptive terrain sensing is essential for rough terrain traversal because it helps legged robots to negotiate individual steps by reacting to terrain irregularities. In this work, we propose to utilize inertial data in the detection of the contact between the leg and the terrain during the stride phase of the leg. We show that relatively cheap accelerometers can be utilized to reliably detect a foot-strike, and thus allow the robot to crawl irregular terrains. The continuous data processing is compared with the interrupt mode in which data are provided only around the foot-strike event. The interrupt mode exhibits significantly better performance, and it also supports generalization of the foot-strike event detector learned from data collected in slow locomotion to faster locomotion where the signals slightly change. The proposed solution is experimentally validated using a real hexapod walking robot for which the walking speed has been improved in comparison to the previous adaptive motion gait based on a force threshold-based position controller for the foot-strike detection.

Název v anglickém jazyce

Online Foot-Strike Detection Using Inertial Measurements for Multi-Legged Walking Robots

Popis výsledku anglicky

Proprioceptive terrain sensing is essential for rough terrain traversal because it helps legged robots to negotiate individual steps by reacting to terrain irregularities. In this work, we propose to utilize inertial data in the detection of the contact between the leg and the terrain during the stride phase of the leg. We show that relatively cheap accelerometers can be utilized to reliably detect a foot-strike, and thus allow the robot to crawl irregular terrains. The continuous data processing is compared with the interrupt mode in which data are provided only around the foot-strike event. The interrupt mode exhibits significantly better performance, and it also supports generalization of the foot-strike event detector learned from data collected in slow locomotion to faster locomotion where the signals slightly change. The proposed solution is experimentally validated using a real hexapod walking robot for which the walking speed has been improved in comparison to the previous adaptive motion gait based on a force threshold-based position controller for the foot-strike detection.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA18-18858S" target="_blank" >GA18-18858S: Metody kontinuálního učení řízení pohybu vícenohých kráčejích robotů v úlohách autonomního sběru dat</a><br>

Návaznosti

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

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

ISBN

978-1-5386-8094-0

ISSN

2153-0858

e-ISSN

2153-0866

Počet stran výsledku

6

Strana od-do

7622-7627

Název nakladatele

IEEE Press

Místo vydání

New York

Místo konání akce

Madrid

Datum konání akce

1. 10. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000458872706134