A Forward / Inverse Motor Controller for Cognitive Robotics
V. Mohan, and P. Morasso. Artificial Neural Networks - ICANN 2006, (2006)
Abstract
Before making a movement aimed at achieving a task, human beings
either run a mental process that attempts to find a feasible course
of action (at the
same time, it must be compatible with a number of internal and external
constraints and near-optimal according to some criterion) or select
it from a
repertoire of previously learned actions, according to the parameters
of the task.
If neither reasoning process succeeds, a typical backup strategy is
to look for a
tool that might allow the operator to match all the task constraints.
A cognitive
robot should support a similar reasoning system. A central element
of this
architecture is a coupled pair of controllers: FMC (forward motor
controller: it
maps tentative trajectories in the joint space into the corresponding
trajectories of
the end-effector variables in the workspace) and IMC (inverse motor
controller:
it maps desired trajectories of the end-effector into feasible trajectories
in the
joint space). The proposed FMC/IMC architecture operates with any
degree of
redundancy and can deal with geometric constraints (range of motion
in the joint
space, internal and external constraints in the workspace) and effort-related
constraints (range of torque of the actuators, etc.). It operates
by alternating two
basic operations: 1) relaxation in the configuration space (for reaching
a target
pose); 2) relaxation in the null space of the kinematic transformation
(for
producing the required interaction force). The failure of either relaxation
can
trigger a higher level of reasoning. For both elements of the architecture
we
propose a closed-form solution and a solution based on ANNs.
%0 Journal Article
%1 Mohan:2006
%A Mohan, V.
%A Morasso, P.
%D 2006
%J Artificial Neural Networks - ICANN 2006
%K imported
%P 602-611
%T A Forward / Inverse Motor Controller for Cognitive Robotics
%X Before making a movement aimed at achieving a task, human beings
either run a mental process that attempts to find a feasible course
of action (at the
same time, it must be compatible with a number of internal and external
constraints and near-optimal according to some criterion) or select
it from a
repertoire of previously learned actions, according to the parameters
of the task.
If neither reasoning process succeeds, a typical backup strategy is
to look for a
tool that might allow the operator to match all the task constraints.
A cognitive
robot should support a similar reasoning system. A central element
of this
architecture is a coupled pair of controllers: FMC (forward motor
controller: it
maps tentative trajectories in the joint space into the corresponding
trajectories of
the end-effector variables in the workspace) and IMC (inverse motor
controller:
it maps desired trajectories of the end-effector into feasible trajectories
in the
joint space). The proposed FMC/IMC architecture operates with any
degree of
redundancy and can deal with geometric constraints (range of motion
in the joint
space, internal and external constraints in the workspace) and effort-related
constraints (range of torque of the actuators, etc.). It operates
by alternating two
basic operations: 1) relaxation in the configuration space (for reaching
a target
pose); 2) relaxation in the null space of the kinematic transformation
(for
producing the required interaction force). The failure of either relaxation
can
trigger a higher level of reasoning. For both elements of the architecture
we
propose a closed-form solution and a solution based on ANNs.
@article{Mohan:2006,
abstract = {Before making a movement aimed at achieving a task, human beings
either run a mental process that attempts to find a feasible course
of action (at the
same time, it must be compatible with a number of internal and external
constraints and near-optimal according to some criterion) or select
it from a
repertoire of previously learned actions, according to the parameters
of the task.
If neither reasoning process succeeds, a typical backup strategy is
to look for a
tool that might allow the operator to match all the task constraints.
A cognitive
robot should support a similar reasoning system. A central element
of this
architecture is a coupled pair of controllers: FMC (forward motor
controller: it
maps tentative trajectories in the joint space into the corresponding
trajectories of
the end-effector variables in the workspace) and IMC (inverse motor
controller:
it maps desired trajectories of the end-effector into feasible trajectories
in the
joint space). The proposed FMC/IMC architecture operates with any
degree of
redundancy and can deal with geometric constraints (range of motion
in the joint
space, internal and external constraints in the workspace) and effort-related
constraints (range of torque of the actuators, etc.). It operates
by alternating two
basic operations: 1) relaxation in the configuration space (for reaching
a target
pose); 2) relaxation in the null space of the kinematic transformation
(for
producing the required interaction force). The failure of either relaxation
can
trigger a higher level of reasoning. For both elements of the architecture
we
propose a closed-form solution and a solution based on ANNs.},
added-at = {2009-06-26T15:25:19.000+0200},
author = {Mohan, V. and Morasso, P.},
biburl = {https://www.bibsonomy.org/bibtex/2ff6b8b7a6dc7826f2f890822c1ce8a8d/butz},
description = {diverse cognitive systems bib},
interhash = {f4bf57b737617edaedc2038a87c69b9e},
intrahash = {ff6b8b7a6dc7826f2f890822c1ce8a8d},
journal = {Artificial Neural Networks - ICANN 2006},
keywords = {imported},
owner = {butz},
pages = {602-611},
timestamp = {2009-06-26T15:25:47.000+0200},
title = { A Forward / Inverse Motor Controller for Cognitive Robotics},
year = 2006
}