Our recently developed Reverse Priority (RP) redundancy resolution method is extended here to the presence of unilateral constraints. The RP method computes the solution to a stack of prioritized tasks starting from the lowest priority one, and adding iteratively the contributions of higher priority tasks. In this framework, unilateral constraints can be added efficiently, while guaranteeing also continuity of joint velocity commands. Since unilateral (hard) constraints are typically placed at the highest priority levels, their treatment within the RP method leads to the least possible modification of the solution computed so far, when analyzing the need to activate or not these constraints. The effectiveness of the approach is shown by simulations on a planar 6R robot and on a humanoid robot, as well as experiments on a KUKA LWR manipulator.
Unilateral constraints in the Reverse Priority redundancy resolution method / Flacco, Fabrizio; DE LUCA, Alessandro. - ELETTRONICO. - (2015), pp. 2564-2571. (Intervento presentato al convegno 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems tenutosi a Hamburg; Germany nel October 2015) [10.1109/IROS.2015.7353726].
Unilateral constraints in the Reverse Priority redundancy resolution method
FLACCO, FABRIZIO;DE LUCA, Alessandro
2015
Abstract
Our recently developed Reverse Priority (RP) redundancy resolution method is extended here to the presence of unilateral constraints. The RP method computes the solution to a stack of prioritized tasks starting from the lowest priority one, and adding iteratively the contributions of higher priority tasks. In this framework, unilateral constraints can be added efficiently, while guaranteeing also continuity of joint velocity commands. Since unilateral (hard) constraints are typically placed at the highest priority levels, their treatment within the RP method leads to the least possible modification of the solution computed so far, when analyzing the need to activate or not these constraints. The effectiveness of the approach is shown by simulations on a planar 6R robot and on a humanoid robot, as well as experiments on a KUKA LWR manipulator.File | Dimensione | Formato | |
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