activity
20182022
most citedGenerative grasp synthesis from demonstration using parametric mixtures

4 citations · 10 across the 6 of their papers we have counts for

collaborators

11 papers

cs.RO20222 cited

BURG-Toolkit: Robot Grasping Experiments in Simulation and the Real World

Martin Rudorfer, Markus Suchi, Mohan Sridharan +2

This paper presents BURG-Toolkit, a set of open-source tools for Benchmarking and Understanding Robotic Grasping. Our tools allow researchers to: (1) create virtual scenes for gene…

cs.RO2022

Generating Task-specific Robotic Grasps

Mark Robson, Mohan Sridharan

This paper describes a method for generating robot grasps by jointly considering stability and other task and object-specific constraints. We introduce a three-level representation…

cs.AI20223 cited

Combining Commonsense Reasoning and Knowledge Acquisition to Guide Deep Learning in Robotics

Mohan Sridharan, Tiago Mota

Algorithms based on deep network models are being used for many pattern recognition and decision-making tasks in robotics and AI. Training these models requires a large labeled dat…

cs.CL2022

The Ninth Advances in Cognitive Systems (ACS) Conference

Mark Burstein, Mohan Sridharan, David McDonald

ACS is an annual meeting for research on the initial goals of artificial intelligence and cognitive science, which aimed to explain the mind in computational terms and to reproduce…

cs.RO20211 cited

Towards a Framework for Changing-Contact Robot Manipulation

Saif Sidhik, Mohan Sridharan, Dirk Ruiken

Many robot manipulation tasks require the robot to make and break contact with objects and surfaces. The dynamics of such changing-contact robot manipulation tasks are discontinuou…

cs.RO2021

Continual Learning of Knowledge Graph Embeddings

Angel Daruna, Mehul Gupta, Mohan Sridharan +1

In recent years, there has been a resurgence in methods that use distributed (neural) representations to represent and reason about semantic knowledge for robotics applications. Ho…