Knot planning from observation

By Takuma Morita, J. Takamatsu, K. Ogawara, Hiroshi Kimura, Katsushi Ikeuchi. 2003

82 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering

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Citations in the corpus

Combining self-supervised learning and imitation for vision-based rope manipulation (2017, background): “[6] developed a system for tying knots from visual observations that makes use of knot theory [25] to identify a sequence of knot states and then execute motor primitives to achieve these states.”
Learning from Demonstrations Through the Use of Non-rigid Registration (2013, background): “Researchers have addressed the problemwithmotion planning [12, 13], learning from observation (using knot theoretic representations) [14], robotic hands with tactile feedback [15], and fixtures that enable robust open-loop”
Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks (2020, background): “Rope has been extensively explored in early robotics literature, such as for knot-tying [27], [45].”
Self-Supervised Learning of State Estimation for Manipulating Deformable Linear Objects (2019, methodology): “This visual perception task has previously been tackled by hand-engineered image processing algorithms, e.g. in [7].”
Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data (2020, background): “manipulation [18, 25, 27, 40], but these techniques can fail to generalize to novel configurations.”
One-handed knotting of a flexible rope with a high-speed multifingered hand having tactile sensors (2007, methodology): “Morita et al. suggested a knot planning method based on human demonstrations by using a system called Knot Planning from Observation (KPO) [7].”
Cable manipulation with a tactile-reactive gripper (2019, background): “of 0.5 cm/s, compared to 6.5 cm/s in our work. B. Cable/rope manipulation Manipulating deformable linear objects has attracted attention in the robotics community [9] with tasks including tying knots [10,11], surgical suturing [12], or wire reshaping [1,2,3]. Due to their high dimensional dynamics, ”
Manipulation Planning for Deformable Linear Objects (2007, background): “Its applications in robotics include the work presented in [20], where the topological state of a DLO is represented by a sequence of signed crossings.”
Knotting/Unknotting Manipulation of Deformable Linear Objects (2006, methodology): “Morita et al. (2003) have been developing a system for knot planning from observation of human demonstrations.”
Motion planning for robotic manipulation of deformable linear objects (2006, methodology): “Its applications in robotics include work presented in [12].”