TY - GEN
T1 - Robot team teleoperation for cooperative manipulation using wearable haptics
AU - Music, Selma
AU - Salvietti, Gionata
AU - Budde Gen Dohmann, Pablo
AU - Chinello, Francesco
AU - Prattichizzo, Domenico
AU - Hirche, Sandra
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/13
Y1 - 2017/12/13
N2 - Robot teams require planning and adaptive capabilities in order to perform cooperative manipulation tasks in dynamic or unstructured environments. Since these capabilities are inherent to humans, it is suitable to consider human-robot team teleoperation for cooperative manipulation where a single human collaborates with the robot team. In this paper, we present a subtask-based control approach which enables a simultaneous execution of two subtasks by the robot team, interacting with the object: trajectory tracking and formation preservation. Control inputs for both subtasks are provided by the human operator. The commands are projected onto the spaces of subtasks using a command mapping strategy. Analogously, measured interacting forces are projected onto the space of feedback signals, provided to the human via wearable fingertip haptic devices through a feedback mapping strategy. Experimental results validate the proposed approach.
AB - Robot teams require planning and adaptive capabilities in order to perform cooperative manipulation tasks in dynamic or unstructured environments. Since these capabilities are inherent to humans, it is suitable to consider human-robot team teleoperation for cooperative manipulation where a single human collaborates with the robot team. In this paper, we present a subtask-based control approach which enables a simultaneous execution of two subtasks by the robot team, interacting with the object: trajectory tracking and formation preservation. Control inputs for both subtasks are provided by the human operator. The commands are projected onto the spaces of subtasks using a command mapping strategy. Analogously, measured interacting forces are projected onto the space of feedback signals, provided to the human via wearable fingertip haptic devices through a feedback mapping strategy. Experimental results validate the proposed approach.
UR - http://www.scopus.com/inward/record.url?scp=85033996818&partnerID=8YFLogxK
U2 - 10.1109/IROS.2017.8206077
DO - 10.1109/IROS.2017.8206077
M3 - Conference contribution
AN - SCOPUS:85033996818
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 2556
EP - 2563
BT - IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017
Y2 - 24 September 2017 through 28 September 2017
ER -