TY - GEN
T1 - Task specific cooperative grasp planning for decentralized multi-robot systems
AU - Muthusamy, Rajkumar
AU - Bechlioulis, Charalampos P.
AU - Kyriakopoulos, Kostas J.
AU - Kyrki, Ville
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/29
Y1 - 2015/6/29
N2 - Grasp planning in multi-robot systems is usually studied in a centralized setting with all robots sharing common knowledge about the overall system. Relaxing this assumption would allow multiple mobile manipulators to cooperate even without strict and precise coordination. Moreover, most typical tasks for cooperative settings, such as transporting heavy objects, require certain forces/torques to be exerted along/around particular directions, for instance, compensating for the weight of the transported object. In this paper, we propose task specific multi-robot grasp planning strategies that allow decentralized planning. Each agent plans its own actions without precise information about the other's plans. The approach is based on analysing a task specific grasp quality metric in a probabilistic context, compensating thus for the incomplete knowledge. Results from simulation experiments demonstrate that task independent planning is clearly inferior when task characteristics are known and thus task specific quality measures should be used. Furthermore, the proposed decentralized planning approaches clearly outperform the baseline and show close to globally optimal performance.
AB - Grasp planning in multi-robot systems is usually studied in a centralized setting with all robots sharing common knowledge about the overall system. Relaxing this assumption would allow multiple mobile manipulators to cooperate even without strict and precise coordination. Moreover, most typical tasks for cooperative settings, such as transporting heavy objects, require certain forces/torques to be exerted along/around particular directions, for instance, compensating for the weight of the transported object. In this paper, we propose task specific multi-robot grasp planning strategies that allow decentralized planning. Each agent plans its own actions without precise information about the other's plans. The approach is based on analysing a task specific grasp quality metric in a probabilistic context, compensating thus for the incomplete knowledge. Results from simulation experiments demonstrate that task independent planning is clearly inferior when task characteristics are known and thus task specific quality measures should be used. Furthermore, the proposed decentralized planning approaches clearly outperform the baseline and show close to globally optimal performance.
UR - http://www.scopus.com/inward/record.url?scp=84938277938&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84938277938&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2015.7140050
DO - 10.1109/ICRA.2015.7140050
M3 - Conference contribution
AN - SCOPUS:84938277938
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 6066
EP - 6073
BT - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Y2 - 26 May 2015 through 30 May 2015
ER -