Learning of grasp adaptation through experience and tactile sensing
By Miao Li, Yasemin Bekiroglu, Danica Kragic, Aude Gemma Billard. 2014
133 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Control and Systems Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sergey Levine
- Pieter Abbeel
- Chelsea Finn
- Trevor Darrell
- Yoshua Bengio
- Ruslan Salakhutdinov
- Abhinav Kumar Gupta
- Quoc V. Le
In Control and Systems Engineering
- Sergey Levine
- Pieter Abbeel
- Chelsea Finn
- Gerhard Neumann
- Jan Peters
- Jitendra Malik
- Abhishek Gupta
- Vikash Kumar
Citations in the corpus
- Solving Rubik's Cube with a Robot Hand (2019, neutral): “tactile sensing [104, 59, 60, 61].”
- Learning dexterous in-hand manipulation (2018, background): “12 Other approaches take a closed-loop approach to dexterous manipulation and incorporate sensor feedback during execution, e.g. tactile sensing [60, 34, 35, 36].”
- Learning robot in-hand manipulation with tactile features (2015, background): “can also aid by detecting grasp instabilities and slippage that can occur while manipulating an object [13, 20, 24, 25].”
- Electronic skins and machine learning for intelligent soft robots (2020, background): “Grasp force optimization and stabilization is one of the most basic manipulation tasks involving tactile sensors (82).”
- Robotic Tactile Perception of Object Properties: A Review (2017, methodology): “In [119], PCA is applied to reduce the dimensionality of tactile readings.”
- Trends and challenges in robot manipulation (2019, background): “[Reproduced from (17, 33)] (C) A soft, foldable gripper that can adapt shape and stiffness.”
- The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes? (2017, unknown): “[26] proposed incorporating tactile readings into dynamics models of objects for a dexterous hand.”
- More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch (2018, background): “[19] incorporated tactile readings into dynamics models of objects for a dexterous hand, thereby adapting the grasp.”
- Learning Dexterous In-Hand Manipulation. (2018, unknown): “tactile sensing [60, 34, 35, 36].”
- Hierarchical Fingertip Space: A Unified Framework for Grasp Planning and In-Hand Grasp Adaptation (2016, methodology): “Finger gaiting may be further required when applying higher grasping force does not suffice [9], [54].”