15 citations · 61 across the 23 of their papers we have counts for
26 papers
CLIPGraphs: Multimodal Graph Networks to Infer Object-Room Affinities
Ayush Agrawal, Raghav Arora, Ahana Datta +5
This paper introduces a novel method for determining the best room to place an object in, for embodied scene rearrangement. While state-of-the-art approaches rely on large language…
Knowledge-based Reasoning and Learning under Partial Observability in Ad Hoc Teamwork
Hasra Dodampegama, Mohan Sridharan
Ad hoc teamwork refers to the problem of enabling an agent to collaborate with teammates without prior coordination. Data-driven methods represent the state of the art in ad hoc te…
Sequence-Agnostic Multi-Object Navigation
Nandiraju Gireesh, Ayush Agrawal, Ahana Datta +4
The Multi-Object Navigation (MultiON) task requires a robot to localize an instance (each) of multiple object classes. It is a fundamental task for an assistive robot in a home or…
RAMP: A Benchmark for Evaluating Robotic Assembly Manipulation and Planning
Jack Collins, Mark Robson, Jun Yamada +3
We introduce RAMP, an open-source robotics benchmark inspired by real-world industrial assembly tasks. RAMP consists of beams that a robot must assemble into specified goal configu…
Toward a Framework for Adaptive Impedance Control of an Upper-limb Prosthesis
Laura Ferrante, Mohan Sridharan, Claudio Zito +1
Adapting upper-limb impedance (i.e., stiffness, damping, inertia) is essential for humans interacting with dynamic environments for executing grasping or manipulation tasks. On the…
Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation
D. A. Sasi Kiran, Kritika Anand, Chaitanya Kharyal +7
This paper describes a framework for the object-goal navigation task, which requires a robot to find and move to the closest instance of a target object class from a random startin…
Object Goal Navigation using Data Regularized Q-Learning
Nandiraju Gireesh, D. A. Sasi Kiran, Snehasis Banerjee +3
Object Goal Navigation requires a robot to find and navigate to an instance of a target object class in a previously unseen environment. Our framework incrementally builds a semant…
Knowledge-based and Data-driven Reasoning and Learning for Ad Hoc Teamwork
Hasra Dodampegama, Mohan Sridharan
We present an architecture for ad hoc teamwork, which refers to collaboration in a team of agents without prior coordination. State of the art methods for this problem often includ…
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…
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…
A Survey of Ad Hoc Teamwork Research
Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman +5
Ad hoc teamwork is the research problem of designing agents that can collaborate with new teammates without prior coordination. This survey makes a two-fold contribution: First, it…
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…
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…
An Adaptive Framework for Reliable Trajectory Following in Changing-Contact Robot Manipulation Tasks
Saif Sidhik, Mohan Sridharan, Dirk Ruiken
We describe a framework for changing-contact robot manipulation tasks that require the robot to make and break contacts with objects and surfaces. The discontinuous interaction dyn…
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…
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…
Axiom Learning and Belief Tracing for Transparent Decision Making in Robotics
Tiago Mota, Mohan Sridharan
A robot's ability to provide descriptions of its decisions and beliefs promotes effective collaboration with humans. Providing such transparency is particularly challenging in inte…
A Survey of Knowledge-based Sequential Decision Making under Uncertainty
Shiqi Zhang, Mohan Sridharan
Reasoning with declarative knowledge (RDK) and sequential decision-making (SDM) are two key research areas in artificial intelligence. RDK methods reason with declarative domain kn…
Non-monotonic Logical Reasoning Guiding Deep Learning for Explainable Visual Question Answering
Heather Riley, Mohan Sridharan
State of the art algorithms for many pattern recognition problems rely on deep network models. Training these models requires a large labeled dataset and considerable computational…
Towards a Theory of Intentions for Human-Robot Collaboration
Rocio Gomez, Mohan Sridharan, Heather Riley
The architecture described in this paper encodes a theory of intentions based on the the key principles of non-procrastination, persistence, and automatically limiting reasoning to…
Generative grasp synthesis from demonstration using parametric mixtures
Ermano Arruda, Claudio Zito, Mohan Sridharan +2
We present a parametric formulation for learning generative models for grasp synthesis from a demonstration. We cast new light on this family of approaches, proposing a parametric…
A Computational Framework for Modelling and Analyzing Ice Storms
Ranjini Swaminathan, Mohan Sridharan, Katharine Hayhoe
Ice storms are extreme weather events that can have devastating implications for the sustainability of natural ecosystems as well as man made infrastructure. Ice storms are caused…
REBA: A Refinement-Based Architecture for Knowledge Representation and Reasoning in Robotics
Mohan Sridharan, Michael Gelfond, Shiqi Zhang +1
This paper describes an architecture for robots that combines the complementary strengths of probabilistic graphical models and declarative programming to represent and reason with…
Mixed Logical and Probabilistic Reasoning for Planning and Explanation Generation in Robotics
Zenon Colaco, Mohan Sridharan
Robots assisting humans in complex domains have to represent knowledge and reason at both the sensorimotor level and the social level. The architecture described in this paper coup…