1987
DOI: 10.1109/jra.1987.1087111
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Redundancy resolution of manipulators through torque optimization

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Cited by 601 publications
(142 citation statements)
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References 15 publications
(3 reference statements)
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“…Let the dynamics of a fully actuated robot in free motion be compactly described by 2 M (q)q + n(q,q) = τ, (6) with positive definite inertia matrix M , Coriolis, centrifugal, and gravitational terms n, and input torque τ ∈ R n . Based on (6), several local optimization-based control schemes have been proposed at the torque level [18][19][20][21] for realizing a desired task acceleration x (possibly including also a PD action on the trajectory error). For instance, at a given robot state (q,q), the solution with minimum torque norm of [18] is given by…”
Section: Redundancy Resolutionmentioning
confidence: 99%
“…Let the dynamics of a fully actuated robot in free motion be compactly described by 2 M (q)q + n(q,q) = τ, (6) with positive definite inertia matrix M , Coriolis, centrifugal, and gravitational terms n, and input torque τ ∈ R n . Based on (6), several local optimization-based control schemes have been proposed at the torque level [18][19][20][21] for realizing a desired task acceleration x (possibly including also a PD action on the trajectory error). For instance, at a given robot state (q,q), the solution with minimum torque norm of [18] is given by…”
Section: Redundancy Resolutionmentioning
confidence: 99%
“…The constraint used here is obstacle avoidance in ℝ 3 space, which is very popular and practical in many robotic applications. However, there are other constraints like joint limit avoidance, minimum excitation of joints, torque optimization [21], desired velocity/acceleration etc., that can be used based on the application. As an illustration, here we focus on the manipulator avoiding obstacles, while the EE reaches its target.…”
Section: Redundancy Resolution Through Elbow Optimizationmentioning
confidence: 99%
“…1,2 Furthermore, it was used to generate the desired trajectory so as to minimize the drag force 11 and joint torques. 7 The joint trajectories were generated to minimize the restoring moments. 6 Han's algorithm offers the advantage, which it is easy to apply to the real system, because the parameters such as mass, buoyancy, center of mass, and center of buoyancy are more easily and exactly obtained than are hydrodynamic parameters.…”
Section: Nomenclaturementioning
confidence: 99%