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Ha XT, Wu D, Lai CF, Ourak M, Borghesan G, Menciassi A, Poorten EV. Contact Localization of Continuum and Flexible Robot Using Data-Driven Approach. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3176723] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Xuan Thao Ha
- Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Di Wu
- Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | | | - Mouloud Ourak
- Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Gianni Borghesan
- Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Arianna Menciassi
- The BioRobotics Institute, Scuola Superiore Sant–Anna, Pontedera, Italy
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Dehio N, Wang Y, Kheddar A. Dual-Arm Box Grabbing With Impact-Aware MPC Utilizing Soft Deformable End-Effector Pads. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3158433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Niels Dehio
- CNRS-University of Montpellier LIRMM Interactive Digital Humans Group, Montpellier, France
| | - Yuquan Wang
- CNRS-University of Montpellier LIRMM Interactive Digital Humans Group, Montpellier, France
| | - Abderrahmane Kheddar
- CNRS-University of Montpellier LIRMM Interactive Digital Humans Group, Montpellier, France
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Qiao Q, Borghesan G, De Schutter J, Vander Poorten EB. Force from Shape—Estimating the Location and Magnitude of the External Force on Flexible Instruments. IEEE T ROBOT 2021. [DOI: 10.1109/tro.2021.3062504] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Martín-Martín R, Brock O. Coupled recursive estimation for online interactive perception of articulated objects. Int J Rob Res 2019. [DOI: 10.1177/0278364919848850] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
We present online multi-modal perception systems for extracting kinematic and dynamic models of articulated objects from physical interactions with the environment. The systems rely on a RGB-D stream, contact wrenches, and proprioception. The proposed systems share an algorithmic foundation: they are based on an architecture of coupled recursive estimation processes. We present and advocate this architecture as a general, versatile, and robust solution for online interactive perception problems. We validate the architecture in extensive experiments to extract kinematic models interactively, varying the appearance, size, structure, and dynamic properties of objects for different tasks and under different environmental conditions. In addition, we experimentally show that the information acquired by the online perception systems enables robot manipulation of articulated objects. Furthermore, we discuss the relationship between the proposed architecture for robot perception and insights about biological perception systems.
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Affiliation(s)
| | - Oliver Brock
- Robotics and Biology Laboratory, Technische Universität Berlin, Germany
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