Curtis, Aidan

10 publications

CoRL 2025 ARCH: Hierarchical Hybrid Learning for Long-Horizon Contact-Rich Robotic Assembly Jiankai Sun, Aidan Curtis, Yang You, Yan Xu, Michael Koehle, Qianzhong Chen, Suning Huang, Leonidas Guibas, Sachin Chitta, Mac Schwager, Hui Li

ICML 2025 Flow-Based Domain Randomization for Learning and Sequencing Robotic Skills Aidan Curtis, Eric Li, Michael Noseworthy, Nishad Gothoskar, Sachin Chitta, Hui Li, Leslie Pack Kaelbling, Nicole E Carey

CoRL 2025 LLM-Guided Probabilistic Program Induction for POMDP Model Estimation Aidan Curtis, Hao Tang, Thiago Veloso, Kevin Ellis, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling

CoRL 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

AAAI 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

ICLRW 2022 Let’s Handle It: Generalizable Manipulation of Articulated Objects Zhutian Yang, Aidan Curtis

IJCAI 2022 PG3: Policy-Guided Planning for Generalized Policy Generation Ryan Yang, Tom Silver, Aidan Curtis, Tomás Lozano-Pérez, Leslie Pack Kaelbling

ICLR 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

AAAI 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

ICML 2020 Flexible and Efficient Long-Range Planning Through Curious Exploration Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin Feigelis, Daniel Yamins