Tube Acceleration: Robust Dexterous Throwing Against Release Uncertainty
In robotic throwing, the release phase involves complex dynamic interactions due to object deformation and limited gripper opening speed, often resulting in inaccurate and nonrepeatable throws. While data-driven methods can be employed to compensate for the release uncertainty, the generalizability...
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| Veröffentlicht in: | IEEE transactions on robotics Jg. 40; S. 2831 - 2849 |
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| Sprache: | Englisch |
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2024
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| Abstract | In robotic throwing, the release phase involves complex dynamic interactions due to object deformation and limited gripper opening speed, often resulting in inaccurate and nonrepeatable throws. While data-driven methods can be employed to compensate for the release uncertainty, the generalizability of learned models to unseen objects is not guaranteed, and object-specific fine-tuning with new data may be required. This fine-tuning process raises concerns about the scalability of such methods for dexterous throwing, where the robot needs to execute diverse motions for throwing various objects. Instead of case-by-case fine-tuning, we aim at designing throwing motion robust against release uncertainty. We encapsulate all uncertainties resulting from complex contact dynamics in a surrogate model of their resulting effect on gripper opening delay . We introduce the notion of tube acceleration to model the class of constant-acceleration motion in joint space that guarantees a release within the set of valid throwing configurations. We propose a convex relaxation of the primal optimization problem with a tight error bound and evaluate its performance in terms of reliability and efficiency. Results show that the approach offers run-time performance to allow online computation of throws on a 7-DoF robot arm. It achieves a high accuracy and success rate (97% for planar throws) at throwing a variety of complex objects, even when using a simple ballistic model for the object's flying dynamics. |
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| AbstractList | In robotic throwing, the release phase involves complex dynamic interactions due to object deformation and limited gripper opening speed, often resulting in inaccurate and nonrepeatable throws. While data-driven methods can be employed to compensate for the release uncertainty, the generalizability of learned models to unseen objects is not guaranteed, and object-specific fine-tuning with new data may be required. This fine-tuning process raises concerns about the scalability of such methods for dexterous throwing, where the robot needs to execute diverse motions for throwing various objects. Instead of case-by-case fine-tuning, we aim at designing throwing motion robust against release uncertainty. We encapsulate all uncertainties resulting from complex contact dynamics in a surrogate model of their resulting effect on gripper opening delay . We introduce the notion of tube acceleration to model the class of constant-acceleration motion in joint space that guarantees a release within the set of valid throwing configurations. We propose a convex relaxation of the primal optimization problem with a tight error bound and evaluate its performance in terms of reliability and efficiency. Results show that the approach offers run-time performance to allow online computation of throws on a 7-DoF robot arm. It achieves a high accuracy and success rate (97% for planar throws) at throwing a variety of complex objects, even when using a simple ballistic model for the object's flying dynamics. |
| Author | Liu, Yang Billard, Aude |
| Author_xml | – sequence: 1 givenname: Yang orcidid: 0000-0003-2484-610X surname: Liu fullname: Liu, Yang email: yang.liuu@epfl.ch organization: Learning Algorithms and Systems Laboratory (LASA), EPFL, Ecublens, Switzerland – sequence: 2 givenname: Aude orcidid: 0000-0002-7076-8010 surname: Billard fullname: Billard, Aude email: aude.billard@epfl.ch organization: Learning Algorithms and Systems Laboratory (LASA), EPFL, Ecublens, Switzerland |
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| SubjectTerms | Acceleration Deformation Dexterous manipulation dynamic manipulation Dynamics Grippers manipulation planning Manipulator dynamics Performance evaluation Robot arms Robots robust/adaptive control of robotic systems Robustness Throwing Uncertainty |
| Title | Tube Acceleration: Robust Dexterous Throwing Against Release Uncertainty |
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