TY - JOUR
T1 - Path-Constrained Haptic Motion Guidance via Adaptive Phase-Based Admittance Control
AU - Shahriari, Erfan
AU - Svarny, Petr
AU - Birjandi, Seyed Ali Baradaran
AU - Hoffmann, Matej
AU - Haddadin, Sami
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2024
Y1 - 2024
N2 - Robots have surpassedhumans in terms of strength and precision, yet humans retain an unparalleled ability for decision-making in the face of unpredictable disturbances. This article aims to combine the strengths of both entities within a singular task: human motion guidance under strict geometric constraints, particularly adhering to predetermined paths. To tackle this challenge, a modular haptic guidance law is proposed that takes the human-applied wrench as an input. Using an auxiliary variable called phase, the generated desired motion is guaranteed to consistently adhere to the constraint path. It is demonstrated how the guidance policy can be generalized into physically interpretable terms, adjustable either prior to initiating the task or dynamically while the task is in progress. Additionally, an illustrative guidance adaptation policy is showcased that takes into account the human's manipulability. Leveraging passivity analysis, potential sources of instability are pinpointed, and subsequently, overall system stability is ensured by incorporating an augmented virtual energy tank.
AB - Robots have surpassedhumans in terms of strength and precision, yet humans retain an unparalleled ability for decision-making in the face of unpredictable disturbances. This article aims to combine the strengths of both entities within a singular task: human motion guidance under strict geometric constraints, particularly adhering to predetermined paths. To tackle this challenge, a modular haptic guidance law is proposed that takes the human-applied wrench as an input. Using an auxiliary variable called phase, the generated desired motion is guaranteed to consistently adhere to the constraint path. It is demonstrated how the guidance policy can be generalized into physically interpretable terms, adjustable either prior to initiating the task or dynamically while the task is in progress. Additionally, an illustrative guidance adaptation policy is showcased that takes into account the human's manipulability. Leveraging passivity analysis, potential sources of instability are pinpointed, and subsequently, overall system stability is ensured by incorporating an augmented virtual energy tank.
UR - http://www.scopus.com/inward/record.url?scp=85213494674&partnerID=8YFLogxK
U2 - 10.1109/TRO.2024.3521861
DO - 10.1109/TRO.2024.3521861
M3 - Article
AN - SCOPUS:85213494674
SN - 1552-3098
JO - IEEE Transactions on Robotics
JF - IEEE Transactions on Robotics
ER -