Grasp recognition in virtual reality for robot pregrasp planning by demonstration

By J. Aleotti, S. Caselli. 2006

103 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering, Human-Computer Interaction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Sergey Levine
2. Chelsea Finn
3. Pieter Abbeel
4. Frederik D. Ebert
5. Annie Xie
6. Tengyu Ma
7. Vikash Kumar
8. Huazhe Xu

In Mechanical Engineering

1. Chelsea Finn
2. Sergey Levine
3. Annie Xie
4. Yuping Luo
5. Tengyu Ma
6. Peter K. Allen
7. Frederik D. Ebert
8. Matei T. Ciocarlie

In Human-Computer Interaction

1. Peter K. Allen
2. Sergey Levine
3. Chelsea Finn
4. Annie Xie
5. Frederik D. Ebert
6. Matei T. Ciocarlie
7. Abhinav Kumar Gupta
8. Lerrel Pinto

Citations in the corpus

• Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling (2019, background): “, 2017, Ye and Alterovitz, 2017, Aleotti and Caselli, 2006, Lawitzky et al., 2012, Torabi et al., 2018, Le et al., 2017, 2018] and many other areas such as playing games [Mnih et al., 2013]. Behavioral cloning [Bain and Sommut, 1999] is one of the underlying central approaches. See Osa et al. [2018]”
• Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight (2019, methodology): “Learning from demonstrations has also been used in combination with planning , where a planning cost function is inferred from data [38, 47, 1, 26] or where tool-use is learned”
• Hand Posture Subspaces for Dexterous Robotic Grasping (2009, methodology): “Aleotti and Caselli (2006) used a Cyberglove to record human grasp trajectories and postures and replicated them on the same target objects using NURBS.”