Aidan Curtis

35 papers A* 10B 2Misc 1Journal 20Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Follow the Signs: Using Textual Cues and LLMs to Guide Efficient Robot Navigation.
CoRR
Jing Cao, Nishanth Kumar, Aidan Curtis
2025 B conf
Cognitive maps are generative programs.
CogSci
Marta Kryven, Cole Wyeth, Aidan Curtis, Kevin Elllis
2025 J jnl
Cognitive maps are generative programs.
CoRR
Marta Kryven, Cole Wyeth, Aidan Curtis, Kevin Ellis
2025 A* conf
Flow-based Domain Randomization for Learning and Sequencing Robotic Skills.
ICML
Aidan Curtis, Eric Li, Michael Noseworthy, Nishad Gothoskar, Sachin Chitta, Hui Li, Leslie Pack Kaelbling, Nicole E. Carey
2025 J jnl
Flow-based Domain Randomization for Learning and Sequencing Robotic Skills.
CoRR
Aidan Curtis, Eric Li, Michael Noseworthy, Nishad Gothoskar, Sachin Chitta, Hui Li, Leslie Pack Kaelbling, Nicole Carey
2025 J jnl
LLM-Guided Probabilistic Program Induction for POMDP Model Estimation.
CoRR
Aidan Curtis, Hao Tang, Thiago Veloso, Kevin Ellis, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2025 J jnl
Seeing is Believing: Belief-Space Planning with Foundation Models as Uncertainty Estimators.
CoRR
Linfeng Zhao, Willie McClinton, Aidan Curtis, Nishanth Kumar, Tom Silver, Leslie Pack Kaelbling, Lawson L. S. Wong
2024 J jnl
Hierarchical Hybrid Learning for Long-Horizon Contact-Rich Robotic Assembly.
CoRR
Jiankai Sun, Aidan Curtis, Yang You, Yan Xu, Michael Koehle, Leonidas J. Guibas, Sachin Chitta, Mac Schwager, Hui Li
2024 — conf
Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness.
Robotics: Science and Systems
Aidan Curtis, George Matheos, Nishad Gothoskar, Vikash Mansinghka, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2024 J jnl
Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness.
CoRR
Aidan Curtis, George Matheos, Nishad Gothoskar, Vikash Mansinghka, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2024 J jnl
Towards Practical Finite Sample Bounds for Motion Planning in TAMP.
CoRR
Seiji Shaw, Aidan Curtis, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy
2024 Misc conf
Trust the PRoC3S: Solving Long-Horizon Robotics Problems with LLMs and Constraint Satisfaction.
CoRL
Aidan Curtis, Nishanth Kumar, Jing Cao, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2024 J jnl
Trust the PRoC3S: Solving Long-Horizon Robotics Problems with LLMs and Constraint Satisfaction.
CoRR
Aidan Curtis, Nishanth Kumar, Jing Cao, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2023 J jnl
Bayes3D: fast learning and inference in structured generative models of 3D objects and scenes.
CoRR
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
2023 A* conf
Task-Directed Exploration in Continuous POMDPs for Robotic Manipulation of Articulated Objects.
ICRA
Aidan Curtis, Leslie Pack Kaelbling, Siddarth Jain
2023 A* conf
Visibility-Aware Navigation Among Movable Obstacles.
ICRA
Jose Muguira-Iturralde, Aidan Curtis, Yilun Du, Leslie Pack Kaelbling, Tomás Lozano-Pérez
2022 A* conf
Discovering State and Action Abstractions for Generalized Task and Motion Planning.
AAAI
Aidan Curtis, Tom Silver, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2022 B conf
Efficient exploration of spatial environments through Map Induction using adaptable compositional map representations.
CogSci
Sugandha Sharma, Aidan Curtis, Marta Kryven, Josh Tenenbaum, Ila Fiete
2022 J jnl
Let's Handle It: Generalizable Manipulation of Articulated Objects.
CoRR
Zhutian Yang, Aidan Curtis
2022 A* conf
Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances.
ICRA
Aidan Curtis, Xiaolin Fang, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Caelan Reed Garrett
2022 A* conf
Map Induction: Compositional spatial submap learning for efficient exploration in novel environments.
ICLR
Sugandha Sharma, Aidan Curtis, Marta Kryven, Joshua B. Tenenbaum, Ila R. Fiete
2022 A* conf
PG3: Policy-Guided Planning for Generalized Policy Generation.
IJCAI
Ryan Yang, Tom Silver, Aidan Curtis, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2022 J jnl
PG3: Policy-Guided Planning for Generalized Policy Generation.
CoRR
Ryan Yang, Tom Silver, Aidan Curtis, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2022 J jnl
Task-Directed Exploration in Continuous POMDPs for Robotic Manipulation of Articulated Objects.
CoRR
Aidan Curtis, Leslie Pack Kaelbling, Siddarth Jain
2022 J jnl
Visibility-Aware Navigation Among Movable Obstacles.
CoRR
Jose Muguira-Iturralde, Aidan Curtis, Yilun Du, Leslie Pack Kaelbling, Tomás Lozano-Pérez
2021 J jnl
Discovering State and Action Abstractions for Generalized Task and Motion Planning.
CoRR
Aidan Curtis, Tom Silver, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2021 J jnl
Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances.
CoRR
Aidan Curtis, Xiaolin Fang, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Caelan Reed Garrett
2021 J jnl
Map Induction: Compositional spatial submap learning for efficient exploration in novel environments.
CoRR
Sugandha Sharma, Aidan Curtis, Marta Kryven, Joshua B. Tenenbaum, Ila R. Fiete
2021 A* conf
Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks.
AAAI
Tom Silver, Rohan Chitnis, Aidan Curtis, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2021 — conf
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation.
NeurIPS Datasets and Benchmarks
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
2020 A* conf
Flexible and Efficient Long-Range Planning Through Curious Exploration.
ICML
Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin T. Feigelis, Daniel Yamins
2020 J jnl
Flexible and Efficient Long-Range Planning Through Curious Exploration.
CoRR
Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin T. Feigelis, Daniel Yamins
2020 J jnl
Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks.
CoRR
Tom Silver, Rohan Chitnis, Aidan Curtis, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling
2020 J jnl
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation.
CoRR
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
2019 A* conf
HealthSense: Software-defined Mobile-based Clinical Trials.
MobiCom
Aidan Curtis, Amruta Pai, Jian Cao, Nidal Moukaddam, Ashutosh Sabharwal