TY - GEN
T1 - Enabling Shared-Control for A Riding Ballbot System
AU - Chen, Yu
AU - Mansouri, Mahshid
AU - Xiao, Chenzhang
AU - Wang, Ze
AU - Hsiao-Wecksler, Elizabeth T.
AU - Norris, William Robert
N1 - This work was supported by NSF NRI-2.0 #2024905. The authors would like to thank NSF NRI for funding this project (Grant #2024905). Special thanks to Yixiao Liu, Keona Banks, Tianyi Han, Zhanpeng Li, Yintao Zhou, and Tommy Nguyen, Maxine He, Jason Robinson, Zhongchun Yu, Prof. Joao Ramos, Prof. Katie Driggs-Campbell, Adam Bleakney, DRES and Center for Autonomy Robotics Lab at UIUC.
PY - 2025
Y1 - 2025
N2 - This study introduces a shared-control approach for collision avoidance in the self-balancing riding ballbot, PURE, marked by its dynamic stability, omnidirectional movement, and hands-free interface. Integrating a sensor array with a novel Passive Artificial Potential Field (PAPF) method, PURE provides intuitive navigation with deceleration assistance and haptic/audio feedback, effectively mitigating collision risks. This approach addresses the limitations of traditional APF methods, such as control oscillations and unnecessary speed reduction in challenging scenarios. A human subject test, with 20 manual wheelchair users and able-bodied individuals, was conducted to evaluate the performance of indoor navigation and obstacle avoidance with the proposed shared-control algorithm. Results showed that shared-control significantly reduced collisions and cognitive load without affecting travel speed, offering intuitive and safe operation. These findings highlight the shared-control system's suitability for enhancing collision avoidance in self-balancing mobility devices, a relatively unexplored area in assistive mobility research.
AB - This study introduces a shared-control approach for collision avoidance in the self-balancing riding ballbot, PURE, marked by its dynamic stability, omnidirectional movement, and hands-free interface. Integrating a sensor array with a novel Passive Artificial Potential Field (PAPF) method, PURE provides intuitive navigation with deceleration assistance and haptic/audio feedback, effectively mitigating collision risks. This approach addresses the limitations of traditional APF methods, such as control oscillations and unnecessary speed reduction in challenging scenarios. A human subject test, with 20 manual wheelchair users and able-bodied individuals, was conducted to evaluate the performance of indoor navigation and obstacle avoidance with the proposed shared-control algorithm. Results showed that shared-control significantly reduced collisions and cognitive load without affecting travel speed, offering intuitive and safe operation. These findings highlight the shared-control system's suitability for enhancing collision avoidance in self-balancing mobility devices, a relatively unexplored area in assistive mobility research.
KW - Force Feedback
KW - Human Performance Augmentation
KW - Human-Centered Robotics
KW - Obstacle Avoidance
KW - Physical Human-Robot Interaction
KW - Shared-Control
UR - https://www.scopus.com/pages/publications/105018302852
UR - https://www.scopus.com/pages/publications/105018302852#tab=citedBy
U2 - 10.1109/CASE58245.2025.11164039
DO - 10.1109/CASE58245.2025.11164039
M3 - Conference contribution
AN - SCOPUS:105018302852
T3 - IEEE International Conference on Automation Science and Engineering
SP - 858
EP - 865
BT - 2025 IEEE 21st International Conference on Automation Science and Engineering, CASE 2025
PB - IEEE Computer Society
T2 - 21st IEEE International Conference on Automation Science and Engineering, CASE 2025
Y2 - 17 August 2025 through 21 August 2025
ER -