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papers

Publications (56)

cs.RO2024

Learning to Bridge the Gap: Efficient Novelty Recovery with Planning and Reinforcement Learning

Alicia Li, Nishanth Kumar, Tomás Lozano-Pérez +1

cs.RO2025

SceneComplete: Open-World 3D Scene Completion in Cluttered Real World Environments for Robot Manipulation

Aditya Agarwal, Gaurav Singh, Bipasha Sen +2

cs.RO2025

One-Shot Manipulation Strategy Learning by Making Contact Analogies

Yuyao Liu, Jiayuan Mao, Joshua Tenenbaum +2

cs.AI2016

Focused Model-Learning and Planning for Non-Gaussian Continuous State-Action Systems

Zi Wang, Stefanie Jegelka, Leslie Pack Kaelbling +1

cs.RO2024

Guiding Long-Horizon Task and Motion Planning with Vision Language Models

Zhutian Yang, Caelan Garrett, Dieter Fox +2

cs.RO2021

Specifying and achieving goals in open uncertain robot-manipulation domains

Leslie Pack Kaelbling, Alex LaGrassa, Tomás Lozano-Pérez

cs.RO2024

Keypoint Abstraction using Large Models for Object-Relative Imitation Learning

Xiaolin Fang, Bo-Ruei Huang, Jiayuan Mao +4

cs.LG2024

What Planning Problems Can A Relational Neural Network Solve?

Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum +1

cs.RO2020

Visual Prediction of Priors for Articulated Object Interaction

Caris Moses, Michael Noseworthy, Leslie Pack Kaelbling +2

cs.RO2022

Representation, learning, and planning algorithms for geometric task and motion planning

Beomjoon Kim, Luke Shimanuki, Leslie Pack Kaelbling +1

cs.RO2024

Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness

Aidan Curtis, George Matheos, Nishad Gothoskar +4

cs.RO2026

From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models

Ashay Athalye, Nishanth Kumar, Tom Silver +4

cs.RO2026

Open-World Task and Motion Planning via Vision-Language Model Generated Constraints

Nishanth Kumar, William Shen, Fabio Ramos +4

cs.RO2021

Planning for Multi-stage Forceful Manipulation

Rachel Holladay, Tomás Lozano-Pérez, Alberto Rodriguez

cs.AI2018

Learning What Information to Give in Partially Observed Domains

Rohan Chitnis, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.RO2025

Differentiable GPU-Parallelized Task and Motion Planning

William Shen, Caelan Garrett, Nishanth Kumar +5

cs.AI2017

STRIPS Planning in Infinite Domains

Caelan Reed Garrett, Tomás Lozano-Pérez, Leslie Pack Kaelbling

stat.ML2016

Bayesian Optimization with Exponential Convergence

Kenji Kawaguchi, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.AI2019

Learning Quickly to Plan Quickly Using Modular Meta-Learning

Rohan Chitnis, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.AI2015

Object-based World Modeling in Semi-Static Environments with Dependent Dirichlet-Process Mixtures

Lawson L. S. Wong, Thanard Kurutach, Leslie Pack Kaelbling +1

cs.RO2021

Learning When to Quit: Meta-Reasoning for Motion Planning

Yoonchang Sung, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.RO2024

Towards Practical Finite Sample Bounds for Motion Planning in TAMP

Seiji Shaw, Aidan Curtis, Leslie Pack Kaelbling +2

cs.AI2023

Learning Efficient Abstract Planning Models that Choose What to Predict

Nishanth Kumar, Willie McClinton, Rohan Chitnis +3

cs.RO2021

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

Aidan Curtis, Xiaolin Fang, Leslie Pack Kaelbling +2

cs.RO2018

Active model learning and diverse action sampling for task and motion planning

Zi Wang, Caelan Reed Garrett, Leslie Pack Kaelbling +1

cs.RO2021

Learning compositional models of robot skills for task and motion planning

Zi Wang, Caelan Reed Garrett, Leslie Pack Kaelbling +1

cs.RO2025

Streaming Flow Policy: Simplifying diffusion/flow-matching policies by treating action trajectories as flow trajectories

Sunshine Jiang, Xiaolin Fang, Nicholas Roy +3

cs.RO2024

Combining Planning and Diffusion for Mobility with Unknown Dynamics

Yajvan Ravan, Zhutian Yang, Tao Chen +2

cs.RO2023

Robust Planning for Multi-stage Forceful Manipulation

Rachel Holladay, Tomás Lozano-Pérez, Alberto Rodriguez

cs.RO2022

Fully Persistent Spatial Data Structures for Efficient Queries in Path-Dependent Motion Planning Applications

Sathwik Karnik, Tomás Lozano-Pérez, Leslie Pack Kaelbling +1

cs.AI2025

LLM-Guided Probabilistic Program Induction for POMDP Model Estimation

Aidan Curtis, Hao Tang, Thiago Veloso +4

cs.RO2024

Practice Makes Perfect: Planning to Learn Skill Parameter Policies

Nishanth Kumar, Tom Silver, Willie McClinton +5

cs.RO2023

Learning Reusable Manipulation Strategies

Jiayuan Mao, Joshua B. Tenenbaum, Tomás Lozano-Pérez +1

cs.RO2023

Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning

Zhutian Yang, Caelan Reed Garrett, Tomás Lozano-Pérez +2

cs.LG2024

Functional Risk Minimization

Ferran Alet, Clement Gehring, Tomás Lozano-Pérez +3

cs.LG2019

Modular meta-learning

Ferran Alet, Tomás Lozano-Pérez, Leslie P. Kaelbling

cs.RO2019

Sampling-Based Methods for Factored Task and Motion Planning

Caelan Reed Garrett, Tomás Lozano-Pérez, Leslie Pack Kaelbling

cs.RO2024

Embodied Uncertainty-Aware Object Segmentation

Xiaolin Fang, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.AI2023

Learning Rational Subgoals from Demonstrations and Instructions

Zhezheng Luo, Jiayuan Mao, Jiajun Wu +3

cs.RO2023

Compositional Diffusion-Based Continuous Constraint Solvers

Zhutian Yang, Jiayuan Mao, Yilun Du +4

cs.RO2021

Active Learning of Abstract Plan Feasibility

Michael Noseworthy, Caris Moses, Isaiah Brand +4

cs.RO2020

Scalable and Probabilistically Complete Planning for Robotic Spatial Extrusion

Caelan Reed Garrett, Yijiang Huang, Tomás Lozano-Pérez +1

cs.AI2018

Integrating Human-Provided Information Into Belief State Representation Using Dynamic Factorization

Rohan Chitnis, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.RO2024

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

Aidan Curtis, Nishanth Kumar, Jing Cao +2

cs.AI2020

PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning

Caelan Reed Garrett, Tomás Lozano-Pérez, Leslie Pack Kaelbling

cs.AI2023

PDSketch: Integrated Planning Domain Programming and Learning

Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum +1

cs.RO2024

DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability

Xiaolin Fang, Caelan Reed Garrett, Clemens Eppner +3

cs.RO2019

Look before you sweep: Visibility-aware motion planning

Gustavo Goretkin, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.RO2022

Visibility-Aware Navigation Among Movable Obstacles

Jose Muguira-Iturralde, Aidan Curtis, Yilun Du +2

cs.RO2020

Integrated Task and Motion Planning

Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay +4

cs.RO2020

Online Replanning in Belief Space for Partially Observable Task and Motion Problems

Caelan Reed Garrett, Chris Paxton, Tomás Lozano-Pérez +2

cs.RO2026

TiPToP: A Modular Open-Vocabulary Robot Manipulation System That Plans

William Shen, Nishanth Kumar, Sahit Chintalapudi +8

cs.RO2023

Embodied Lifelong Learning for Task and Motion Planning

Jorge Mendez-Mendez, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.RO2017

Provably Safe Robot Navigation with Obstacle Uncertainty

Brian Axelrod, Leslie Pack Kaelbling, Tomás Lozano-Pérez

cs.RO2026

Rational Inverse Reasoning: Few-Shot Imitation by Inferring Intent through Planning

Ben Zandonati, Tomás Lozano-Pérez, Leslie Pack Kaelbling

cs.LG2019

Learning Compact Models for Planning with Exogenous Processes

Rohan Chitnis, Tomás Lozano-Pérez