Ashwin Balakrishna

Orcid: 0000-0002-3508-7850

According to our database1, Ashwin Balakrishna authored at least 43 papers between 2018 and 2024.

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Bibliography

2024
Language-Embedded Gaussian Splats (LEGS): Incrementally Building Room-Scale Representations with a Mobile Robot.
CoRR, 2024

OpenVLA: An Open-Source Vision-Language-Action Model.
CoRR, 2024

CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Driving.
CoRR, 2024

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.
CoRR, 2024

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.
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Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022
Scalable Supervision for Safe and Efficient Online Robot Learning
PhD thesis, 2022

Dynamics-Aware Comparison of Learned Reward Functions.
CoRR, 2022

VisuoSpatial Foresight for physical sequential fabric manipulation.
Auton. Robots, 2022

Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

LEGS: Learning Efficient Grasp Sets for Exploratory Grasping.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Learning Switching Criteria for Sim2Real Transfer of Robotic Fabric Manipulation Policies.
Proceedings of the 18th IEEE International Conference on Automation Science and Engineering, 2022

2021
Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones.
IEEE Robotics Autom. Lett., 2021

MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance.
CoRR, 2021

LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Iterative Tasks.
CoRR, 2021

ABC-LMPC: Safe Sample-Based Learning MPC for Stochastic Nonlinear Dynamical Systems with Adjustable Boundary Conditions.
Proceedings of the Algorithmic Foundations of Robotics XIV, 2021

Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies.
Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Disentangling Dense Multi-Cable Knots.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Policy Gradient Bayesian Robust Optimization for Imitation Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Sparse Reward Iterative Tasks.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

LazyDAgger: Reducing Context Switching in Interactive Imitation Learning.
Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

Kit-Net: Self-Supervised Learning to Kit Novel 3D Objects into Novel 3D Cavities.
Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

2020
Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks.
IEEE Robotics Autom. Lett., 2020

Level-6 Automated IoT integrated with Artificial Intelligence Based Big Data-Driven Dynamic Vehicular Traffic Control System.
EAI Endorsed Trans. Energy Web, 2020

Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects.
CoRR, 2020

Untangling Dense Knots by Learning Task-Relevant Keypoints.
CoRR, 2020

MMGSD: Multi-Modal Gaussian Shape Descriptors for Correspondence Matching in 1D and 2D Deformable Objects.
CoRR, 2020

Learning to Smooth and Fold Real Fabric Using Dense Object Descriptors Trained on Synthetic Color Images.
CoRR, 2020

VisuoSpatial Foresight for Multi-Step, Multi-Task Fabric Manipulation.
Proceedings of the Robotics: Science and Systems XVI, 2020

Deep Imitation Learning of Sequential Fabric Smoothing From an Algorithmic Supervisor.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Untangling Dense Knots by Learning Task-Relevant Keypoints.
Proceedings of the 4th Conference on Robot Learning, 2020

Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects.
Proceedings of the 4th Conference on Robot Learning, 2020

Accelerating Grasp Exploration by Leveraging Learned Priors.
Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020

Orienting Novel 3D Objects Using Self-Supervised Learning of Rotation Transforms.
Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020

2019
Deep Imitation Learning of Sequential Fabric Smoothing Policies.
CoRR, 2019

Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations.
CoRR, 2019

Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter.
Proceedings of the International Conference on Robotics and Automation, 2019

On-Policy Robot Imitation Learning from a Converging Supervisor.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Automating Planar Object Singulation by Linear Pushing with Single-point and Multi-point Contacts.
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

2018
Predicting Electric Vehicle Charging Station Usage: Using Machine Learning to Estimate Individual Station Statistics from Physical Configurations of Charging Station Networks.
CoRR, 2018


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