18 citations · 59 across the 19 of their papers we have counts for
12 papers · 1 filter
Stochastic Action Prediction for Imitation Learning
Sagar Gubbi Venkatesh, Nihesh Rathod, Shishir Kolathaya +1
Imitation learning is a data-driven approach to acquiring skills that relies on expert demonstrations to learn a policy that maps observations to actions. When performing demonstra…
Scene Text Detection for Augmented Reality -- Character Bigram Approach to reduce False Positive Rate
Sagar Gubbi, Bharadwaj Amrutur
Natural scene text detection is an important aspect of scene understanding and could be a useful tool in building engaging augmented reality applications. In this work, we address…
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…
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…
One-Shot Object Localization Using Learnt Visual Cues via Siamese Networks
Sagar Gubbi Venkatesh, Bharadwaj Amrutur
A robot that can operate in novel and unstructured environments must be capable of recognizing new, previously unseen, objects. In this work, a visual cue is used to specify a nove…
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…
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…
Spatial Reasoning from Natural Language Instructions for Robot Manipulation
Sagar Gubbi Venkatesh, Anirban Biswas, Raviteja Upadrashta +3
Robots that can manipulate objects in unstructured environments and collaborate with humans can benefit immensely by understanding natural language. We propose a pipelined architec…
Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach
Kartik Paigwar, Lokesh Krishna, Sashank Tirumala +7
In this paper, with a view toward fast deployment of locomotion gaits in low-cost hardware, we use a linear policy for realizing end-foot trajectories in the quadruped robot, Stoch…
Robust and Scalable Techniques for TWR and TDoA based localization using Ultra Wide Band Radios
Rakshit Ramesh, Aaron John-Sabu, Harshitha S +4
Current trends in autonomous vehicles and their applications indicates an increasing need in positioning at low battery and compute cost. Lidars provide accurate localization at th…
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…
Vermillion: A High-Performance Scalable IoT Middleware for Smart Cities
Poorna Chandra Tejasvi, Vasanth Rajaraman, Arun Babu Puthuparambil +2
With the massive increase in the number of IoT devices being deployed in smart cities, it becomes paramount for middlewares to be able to handle very high loads and support demandi…