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@MISC{Mirrazavi Salehian2018-ID999,
author = {Mirrazavi Salehian, S. S. and Figueroa, N. and Billard, A.},
title = {A Unified Framework for Coordinated Multi-Arm Motion Planning},
howpublished = {The International Journal of Robotics Research},
year = {2018},
abstract = {Coordination is essential in the design of dynamic control strategies for multi-arm robotic systems. Given the complexity
of the task and dexterity of the system, coordination constraints can emerge from different levels of planning and control.
Primarily, one must consider task-space coordination, where the robots must coordinate with each other, with an object
or with a target of interest. Coordination is also necessary in joint-space, as the robots should avoid self-collisions at
any time. We provide such joint-space coordination by introducing a centralized inverse kinematics (IK) solver under
self-collision avoidance constraints; formulated as a quadratic program (QP) and solved in real-time. The space of
free motion is modeled through a sparse non-linear kernel classification method in a data-driven learning approach.
Moreover, we provide multi-arm task-space coordination for both synchronous or asynchronous behaviors. We define
a synchronous behavior as that in which the robot arms must coordinate with each other and with a moving object such
that they reach for it in synchrony. In contrast, an asynchronous behavior allows for each robot to perform independent
point-to-point reaching motions. To transition smoothly from asynchronous to synchronous behaviors and conversely,
we introduce the notion of synchronization allocation.We show how this allocation can be controlled through an external
variable, such as the location of the object to be manipulated. Both behaviors and their synchronization allocation are
encoded in a single dynamical system. We validate our framework on a dual-arm robotic system and demonstrate that
the robots can re-synchronize and adapt the motion of each arm while avoiding self-collision within milliseconds. The
speed of control is exploited to intercept fast moving objects whose motion cannot be predicted accurately.},
}


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