TY - JOUR
T1 - Reconciling Conflicting Intents
T2 - Bidirectional Trust-Based Variable Autonomy for Mobile Robots
AU - Li, Yinglin
AU - Cui, Rongxin
AU - Yan, Weisheng
AU - Zhang, Shi
AU - Yang, Chenguang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2024/6/1
Y1 - 2024/6/1
N2 - In the realm of semi-autonomous mobile robots designed for remote operation with humans, current variable autonomy approaches struggle to reconcile conflicting intents while ensuring compliance, autonomy, and safety. To address this challenge, we propose a bidirectional trust-based variable autonomy (BTVA) control approach. By incorporating diverse trust factors and leveraging Kalman filtering techniques, we establish a core abstraction layer to construct the state-space model of bidirectional computational trust. This bidirectional trust is integrated into the variable autonomy control loop. Real-time modulation of the degree of automation is achieved through variable weight receding horizon optimization. Through a within-group experimental study with twenty participants in a semi-autonomous navigation task, we validate the effectiveness of our method in goal transfer and assisted teleoperation. Statistical analysis reveals that our method achieves a balance between rapid response and trajectory smoothness. Compared with binary control switching, this method reduces operator workload by 14.3% and enhances system usability by 9.9%.
AB - In the realm of semi-autonomous mobile robots designed for remote operation with humans, current variable autonomy approaches struggle to reconcile conflicting intents while ensuring compliance, autonomy, and safety. To address this challenge, we propose a bidirectional trust-based variable autonomy (BTVA) control approach. By incorporating diverse trust factors and leveraging Kalman filtering techniques, we establish a core abstraction layer to construct the state-space model of bidirectional computational trust. This bidirectional trust is integrated into the variable autonomy control loop. Real-time modulation of the degree of automation is achieved through variable weight receding horizon optimization. Through a within-group experimental study with twenty participants in a semi-autonomous navigation task, we validate the effectiveness of our method in goal transfer and assisted teleoperation. Statistical analysis reveals that our method achieves a balance between rapid response and trajectory smoothness. Compared with binary control switching, this method reduces operator workload by 14.3% and enhances system usability by 9.9%.
KW - Bidirectional trust
KW - conflicting intents
KW - degree of automation
KW - human-robot collaboration
KW - variable autonomy
UR - http://www.scopus.com/inward/record.url?scp=85192194579&partnerID=8YFLogxK
U2 - 10.1109/LRA.2024.3396100
DO - 10.1109/LRA.2024.3396100
M3 - 文章
AN - SCOPUS:85192194579
SN - 2377-3766
VL - 9
SP - 5615
EP - 5622
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 6
ER -