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Takanori Ohnuma

dblp:67/9963 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 first-authorHuman-computer interaction and ubiquitous computing · 3 · 2 first-authorApplied, interdisciplinary, general and emerging computing · 2 · 2 first-authorSystems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%
Artificial intelligence
1 paper
Motion planning and robot control · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
assistive robotics
0.112011
JAIST Robotic Walker control based on a two-layered Kalman filter · ICRA 2011
Human-robot interaction
intention recognition
0.112011
JAIST Robotic Walker control based on a two-layered Kalman filter · ICRA 2011
Human-robot interaction › assistive robotics
robotic walker
0.112011
JAIST Robotic Walker control based on a two-layered Kalman filter · ICRA 2011
Robotics › Motion planning and robot control › robot control
motion control
0.012011
JAIST Robotic Walker control based on a two-layered Kalman filter · ICRA 2011

Methods — techniques the papers use, named apart from their topics

leg tracking · 0.2kalman filter · 0.2
YearPublicationVenuePosition
2014 Particle filter based lower limb prediction and motion control for JAIST Active Robotic Walker
abstract
This paper presents an interactive control for our assistive robotic walker, the JAIST Active Robotic Walker (JARoW), developed for elderly people in need of walking assistance. The focus of our paper is placed on how to estimate the user's walking parameters by sensing the locations of lower limbs and to predict his or her walking patterns. For this purpose, a particle-filter-based prediction technique and a motion controller are developed to help JARoW smoothly generate the direction and velocity of its movements in a way that reflects the prediction. The proposed scheme and its implementation are described in detail, and outdoor experiments are performed to demonstrate its effectiveness and feasibility in everyday environments.
Takanori Ohnuma, Geunho Lee 0001, Nak Young Chong
RO-MAN1
2014 Walking Intent-Based Movement Control for JAIST Active Robotic Walker
abstract
This paper presents a novel interactive control for our assistive robotic walker, the JAIST Active Robotic Walker (JARoW), developed for elderly people in need of assistance. The aim of our research is to recognize characteristics of the user's gait and to generate the movement of JARoW accordingly. Specifically, the proposed control enables JARoW to accurately generate the direction and velocity of its movement in a way that corresponds to the user's variable walking behaviors. The algorithm and implementation of the control are explained in detail, and the effectiveness and usability of JARoW are verified through extensive experiments in everyday environments.
Geunho Lee 0001, Takanori Ohnuma, Nak Young Chong, Soon-Geul Lee
IEEE Trans. Syst. Man Cybern. Syst.2
2011 JAIST Robotic Walker control based on a two-layered Kalman filter
abstract
This paper presents a new control scheme of JAIST Active Robotic Walker (JARoW) developed to provide elderly people with sufficient ambulatory capability. Toward its practical use, our focus is placed on how to allow easier and reliable maneuverability by creating a natural user interface. Specifically, our challenge lies in providing a well-functioning controller by detecting what the user wants to do or their intentions. A Kalman filter based tracking scheme is realized to estimate and predict the locations of the user's legs and body in real time. The feedback control can then adjust the motions of JARoW corresponding to the actual user's walking behaviors. Our experiments confirm that JARoW can autonomously adjust its motion direction and velocity without requiring any additional control inputs.
Geunho Lee 0001, Eui-Jung Jung, Takanori Ohnuma, Nak Young Chong, Byung-Ju Yi
ICRA3
2011 Particle filter based feedback control of JAIST Active Robotic Walker
abstract
We present a new control scheme of JAIST Active Robotic Walker (JARoW) developed to provide potential users such as the elderly with sufficient ambulatory capability. Toward its practical use, we tackle JARoW's easy and reliable maneuverability by creating a natural user interface between a user and JARoW. Specifically, our focus is placed on how to realize the natural and smooth movement of JARoW despite different gait parameters of users. For this purpose, a particle filtered interface function (PFIF) is proposed to estimate and predict the locations of the user's legs and body. Then, the simple feedback motion control function adjusts the motions of JARoW corresponding to the estimation and prediction. Experimental results show that the proposed control scheme can be quite satisfactory for practical use without requiring any additional user effort.
Takanori Ohnuma, Geunho Lee 0001, Nak Young Chong
RO-MAN1