Aidan Curtis

According to our database, Aidan Curtis authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Hierarchical Hybrid Learning for Long-Horizon Contact-Rich Robotic Assembly.

Jiankai Sun, Aidan Curtis, Yang You, Yan Xu, Michael Koehle, Leonidas J. Guibas, Sachin Chitta, Mac Schwager, Hui Li

CoRR, 2024

Towards Practical Finite Sample Bounds for Motion Planning in TAMP.

Seiji Shaw, Aidan Curtis, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy

CoRR, 2024

Trust the PRoC3S: Solving Long-Horizon Robotics Problems with LLMs and Constraint Satisfaction.

Aidan Curtis, Nishanth Kumar, Jing Cao, Tomás Lozano-Pérez, Leslie Pack Kaelbling

CoRR, 2024

Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness.

Aidan Curtis, George Matheos, Nishad Gothoskar, Vikash Mansinghka, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling

CoRR, 2024

2023

Bayes3D: fast learning and inference in structured generative models of 3D objects and scenes.

Nishad Gothoskar, Matin Ghavami, Eric Li, Aidan Curtis, Michael Noseworthy, Karen Chung, Brian Patton, William T. Freeman, Joshua B. Tenenbaum, Mirko Klukas, Vikash K. Mansinghka

CoRR, 2023

Visibility-Aware Navigation Among Movable Obstacles.

Jose Muguira-Iturralde, Aidan Curtis, Yilun Du, Leslie Pack Kaelbling, Tomás Lozano-Pérez

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Task-Directed Exploration in Continuous POMDPs for Robotic Manipulation of Articulated Objects.

Aidan Curtis, Leslie Pack Kaelbling, Siddarth Jain

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

Let's Handle It: Generalizable Manipulation of Articulated Objects.

Zhutian Yang, Aidan Curtis

CoRR, 2022

PG3: Policy-Guided Planning for Generalized Policy Generation.

Ryan Yang, Tom Silver, Aidan Curtis, Tomás Lozano-Pérez, Leslie Pack Kaelbling

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances.

Aidan Curtis, Xiaolin Fang, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Caelan Reed Garrett

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Map Induction: Compositional spatial submap learning for efficient exploration in novel environments.

Sugandha Sharma, Aidan Curtis, Marta Kryven, Joshua B. Tenenbaum, Ila R. Fiete

Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient exploration of spatial environments through Map Induction using adaptable compositional map representations.

Sugandha Sharma, Aidan Curtis, Marta Kryven, Josh Tenenbaum, Ila Fiete

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Discovering State and Action Abstractions for Generalized Task and Motion Planning.

Aidan Curtis, Tom Silver, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation.

Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin T. Feigelis, Daniel Bear, Dan Gutfreund, David D. Cox, Antonio Torralba, James J. DiCarlo, Josh Tenenbaum, Josh H. McDermott, Dan Yamins

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks.

Tom Silver, Rohan Chitnis, Aidan Curtis, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation.

Chuang Gan, Jeremy Schwartz, Seth Alter, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Damian Mrowca, Michael Lingelbach, Aidan Curtis, Kevin T. Feigelis, Daniel M. Bear, Dan Gutfreund, David D. Cox, James J. DiCarlo, Josh H. McDermott, Joshua B. Tenenbaum, Daniel L. K. Yamins

CoRR, 2020

Flexible and Efficient Long-Range Planning Through Curious Exploration.

Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin T. Feigelis, Daniel Yamins

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

HealthSense: Software-defined Mobile-based Clinical Trials.

Aidan Curtis, Amruta Pai, Jian Cao, Nidal Moukaddam, Ashutosh Sabharwal

Proceedings of the 25th Annual International Conference on Mobile Computing and Networking, 2019