activity
20242026
collaborators

15 papers

cs.RO2026

Fibration Trees: A Unified Approach to Multi-Robot Motion Planning

Andreas Orthey, Florian T. Pokorny, Lydia E. Kavraki

State space projections and decompositions have emerged as powerful tools to tackle the curse of dimensionality in high-dimensional, multi-robot motion planning problems. However,…

cs.RO2026

Think Fast and Far: Long-Horizon Online POMDP Planning via Rapid State Sampling

Yuanchu Liang, Edward Kim, J. Arden Knoll +4

Partially Observable Markov Decision Processes (POMDPs) are a general and principled framework for motion planning under uncertainty. Despite tremendous improvement in the scalabil…

cs.RO2026

The Open Motion Planning Library 2.0

Weihang Guo, Theodoros Tyrovouzis, Emiliano Flores +5

The Open Motion Planning Library (OMPL), first released in 2008, has become a cornerstone of the motion planning community, providing implementations of a wide range of state-of-th…

cs.RO2026

Ultrafast Sampling-based Kinodynamic Planning via Differential Flatness

Thai Duong, Clayton W. Ramsey, Zachary Kingston +2

Motion planning under dynamics constraints, i.e, kinodynamic planning, enables safe robot operation by generating dynamically feasible trajectories that the robot can accurately tr…

cs.RO2026

Using VLM Reasoning to Constrain Task and Motion Planning

Muyang Yan, Miras Mengdibayev, Ardon Floros +3

In task and motion planning, high-level task planning is done over an abstraction of the world to enable efficient search in long-horizon robotics problems. However, the feasibilit…

cs.RO2026

Python Bindings for a Large C++ Robotics Library: The Case of OMPL

Weihang Guo, Theodoros Tyrovouzis, Lydia E. Kavraki

Python bindings are a critical bridge between high-performance C++ libraries and the flexibility of Python, enabling rapid prototyping, reproducible experiments, and integration wi…