22 citations · 30 across the 10 of their papers we have counts for
10 papers
Model predictive trajectory optimization and tracking for on-road autonomous vehicles
Peng Liu, Brian Paden, Umit Ozguner
Motion planning for autonomous vehicles requires spatio-temporal motion plans (i.e. state trajectories) to account for dynamic obstacles. This requires a trajectory tracking contro…
Accelerated Labeling of Discrete Abstractions for Autonomous Driving Subject to LTL Specifications
Brian Paden, Peng Liu, Schuyler Cullen
Linear temporal logic and automaton-based run-time verification provide a powerful framework for designing task and motion planning algorithms for autonomous agents. The drawback t…
Efficient Nearest-Neighbor Search for Dynamical Systems with Nonholonomic Constraints
Valerio Varricchio, Brian Paden, Dmitry Yershov +1
Nearest-neighbor search dominates the asymptotic complexity of sampling-based motion planning algorithms and is often addressed with k-d tree data structures. While it is generally…
The Generalized Label Correcting Method for Optimal Kinodynamic Motion Planning
Brian Paden
Nearly all autonomous robotic systems use some form of motion planning to compute reference motions through their environment. An increasing use of autonomous robots in a broad ran…
Landmark Guided Probabilistic Roadmap Queries
Brian Paden, Yannik Nager, Emilio Frazzoli
A landmark based heuristic is investigated for reducing query phase run-time of the probabilistic roadmap (\PRM) motion planning method. The heuristic is generated by storing minim…
Design of Admissible Heuristics for Kinodynamic Motion Planning via Sum-of-Squares Programming
Brian Paden, Valerio Varriccho, Emilio Frazzoli
How does one obtain an admissible heuristic for a kinodynamic motion planning problem? This paper develops the analytical tools and techniques to answer this question. A sufficient…