most citedImitation Learning for High Precision Peg-in-Hole Tasks

18 citations · 33 across the 8 of their papers we have counts for

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cs.RO2020

Multi-Instance Aware Localization for End-to-End Imitation Learning

Sagar Gubbi Venkatesh, Raviteja Upadrashta, Shishir Kolathaya +1

Existing architectures for imitation learning using image-to-action policy networks perform poorly when presented with an input image containing multiple instances of the object of…

cs.RO2020★ 18 cited

Imitation Learning for High Precision Peg-in-Hole Tasks

Sagar Gubbi, Shishir Kolathaya, Bharadwaj Amrutur

Industrial robot manipulators are not able to match the precision and speed with which humans are able to execute contact rich tasks even to this day. Therefore, as a means overcom…

cs.RO2020★ 5 cited

Teaching Robots Novel Objects by Pointing at Them

Sagar Gubbi Venkatesh, Raviteja Upadrashta, Shishir Kolathaya +1

Robots that must operate in novel environments and collaborate with humans must be capable of acquiring new knowledge from human experts during operation. We propose teaching a rob…

cs.RO2020

Translating Natural Language Instructions to Computer Programs for Robot Manipulation

Sagar Gubbi Venkatesh, Raviteja Upadrashta, Bharadwaj Amrutur

It is highly desirable for robots that work alongside humans to be able to understand instructions in natural language. Existing language conditioned imitation learning models dire…

cs.RO2020

Learning Stable Manoeuvres in Quadruped Robots from Expert Demonstrations

Sashank Tirumala, Sagar Gubbi, Kartik Paigwar +6

With the research into development of quadruped robots picking up pace, learning based techniques are being explored for developing locomotion controllers for such robots. A key pr…