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Yu Chen 0071

dblp:87/1254-71 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2025
0000-0001-6249-4032ORCID · verified

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

Artificial intelligence and machine learning · 2 · 2 since 2021Systems, architecture and hardware · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

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
2 papers
Human-robot interaction · 54% Accessibility and assistive technology · 31% Interaction techniques and input · 16%
Artificial intelligence
2 papers
Motion planning and robot control · 100%

Topics — the 9 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction › physical human-robot interaction
admittance control
0.912025
An Interactive Hands-Free Controller for a Riding Ballbot to Enable Simple Shared Control Tasks · ICRA 2025
Human-robot interaction
physical human-robot interaction
0.912025
An Interactive Hands-Free Controller for a Riding Ballbot to Enable Simple Shared Control Tasks · ICRA 2025
Human-robot interaction
shared control
0.912025
An Interactive Hands-Free Controller for a Riding Ballbot to Enable Simple Shared Control Tasks · ICRA 2025
Interaction techniques and input › hands-free interaction
hands-free input
0.812024
Driving a Ballbot Wheelchair with Hands-Free Torso Control · HRI 2024
Accessibility and assistive technology
mobility assistance
0.812024
Driving a Ballbot Wheelchair with Hands-Free Torso Control · HRI 2024
Accessibility and assistive technology › mobility assistance
wheelchair control
0.812024
Driving a Ballbot Wheelchair with Hands-Free Torso Control · HRI 2024
Robotics › Motion planning and robot control
robot control
0.312025
An Interactive Hands-Free Controller for a Riding Ballbot to Enable Simple Shared Control Tasks · ICRA 2025
Robotics › Motion planning and robot control › robot control › tracking control
velocity tracking
0.312025
An Interactive Hands-Free Controller for a Riding Ballbot to Enable Simple Shared Control Tasks · ICRA 2025
Robotics › Motion planning and robot control
omnidirectional mobile robot
0.212024
Driving a Ballbot Wheelchair with Hands-Free Torso Control · HRI 2024

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

interaction compensation · 1.7control gain personalization · 1.7admittance control · 1.7user study · 1.5repeated-measures MANOVA · 1.5
YearPublicationVenuePosition
2025 An Interactive Hands-Free Controller for a Riding Ballbot to Enable Simple Shared Control Tasks
abstract
Our team developed a riding ballbot (called PURE) that is dynamically stable, omnidirectional, and driven by lean-to-steer control. A hands-free admittance control scheme (HACS) was previously integrated to allow riders with different torso functions to control the robot's movements via torso leaning and twisting. Such an interface requires motor coordination skills and could result in collisions with obstacles due to low proficiency. Hence, a shared controller (SC) that limits the speed of PURE could be helpful to ensure the safety of riders. However, the self-balancing dynamics of PURE could result in a weak control authority of its motion, in which the torso motion of the rider could easily disturb the tracking of the command speed dictated by the shared controller. Thus, we proposed an interactive hands-free admittance control scheme (iHACS), with the following features to improve the speed-tracking performance of PURE: control gain personalization module and interaction compensation module. Human riding tests of simple tasks, idle-keeping and speed-limiting, were conducted to compare the performance of HACS and iHACS. Two manual wheelchair users and two able-bodied individuals participated in this study. They were instructed to use “adver-sarial” torso motions that would tax the PURE's ability to keep the ballbot idling or below a set speed, i.e., competing objectives between rider and robot. In the idle-keeping tasks, iHACS demonstrated minimal translational motion and low command speed tracking RMSE, even with significant torso lean angles. During the speed-limiting task, where the commanded speed was saturated at 0.5 m/s, the system achieved an average maximum speed of 1.1 m/s with iHACS, compared with that of over 1.9 m/s with HACS. These results suggest that iHACS can enhance PURE's control authority over the rider, which enables PURE to provide physical interactions back to the rider and results in a collaborative rider-robot synergy.
Chenzhang Xiao, Seung Yun Song, Yu Chen 0071, Mahshid Mansouri, João Ramos 0004, William R. Norris 0001, Elizabeth T. Hsiao-Wecksler
ICRA3
2024 Driving a Ballbot Wheelchair with Hands-Free Torso Control
abstract
A novel wheelchair called PURE (Personalized Unique Rolling Experience) that uses hands-free (HF) torso lean-to-steer control has been developed for manual wheelchair users (mWCUs). PURE addresses limitations of current wheelchairs, such as the inability to use both hands for life experiences instead of propulsion. PURE uses a ball-based robot drivetrain to offer a compact, self-balancing, omnidirectional mobile device. A custom sensor system converts rider torso motions into direction and speed commands to control PURE, which is especially useful if a rider has minimal torso range of motion. We explored whether PURE's HF control performed as well as a traditional joystick (JS) human-robot interface and mWCUs, who may have reduced torso motion, performed as well as able-bodied users (ABUs). 10 mWCUs and 10 ABUs were trained and tested to drive PURE through courses replicating indoor environments. Each participant adjusted personal sensitivity settings for both HF and JS control. Repeated-measures MANOVA tests suggested that the effectiveness (number of collisions), efficiency (completion time), comfort (NASA TLX scores except physical demand), and robustness (index of performances) were similar for HF and JS control and between mWCUs and ABUs for all sections. These results suggest that PURE provides an effective method for controlling this new omnidirectional wheelchair by only using torso motion thus leaving both hands to be used for other tasks during propulsion.
Seung Yun Song, Nadja Marin, Chenzhang Xiao, Mahshid Mansouri, João Ramos 0004, Yu Chen 0071, Adam Bleakney, Deana McDonagh, William R. Norris 0001, Jeannette Elliott, Patricia B. Malik, Elizabeth T. Hsiao-Wecksler
HRI6