Ashwin Balakrishna
Orcid: 0000-0002-3508-7850
According to our database1,
Ashwin Balakrishna
authored at least 39 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models.
CoRR, 2024
2022
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
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
IEEE Robotics Autom. Lett., 2021
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
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021
Proceedings of the IEEE International Conference on Robotics and Automation, 2021
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
Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021
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
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
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
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
Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020
Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020
2019
Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations.
CoRR, 2019
Proceedings of the International Conference on Robotics and Automation, 2019
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