2 citations · 3 across the 9 of their papers we have counts for
5 papers · 1 filter
Real-Time Anomaly Detection and Reactive Planning with Large Language Models
Rohan Sinha, Amine Elhafsi, Christopher Agia +3
Foundation models, e.g., large language models (LLMs), trained on internet-scale data possess zero-shot generalization capabilities that make them a promising technology towards de…
ZAPP! Zonotope Agreement of Prediction and Planning for Continuous-Time Collision Avoidance with Discrete-Time Dynamics
Luca Paparusso, Shreyas Kousik, Edward Schmerling +2
The past few years have seen immense progress on two fronts that are critical to safe, widespread mobile robot deployment: predicting uncertain motion of multiple agents, and plann…
Refining Obstacle Perception Safety Zones via Maneuver-Based Decomposition
Sever Topan, Yuxiao Chen, Edward Schmerling +4
A critical task for developing safe autonomous driving stacks is to determine whether an obstacle is safety-critical, i.e., poses an imminent threat to the autonomous vehicle. Our…
Real-Time Stochastic Kinodynamic Motion Planning via Multiobjective Search on GPUs
Brian Ichter, Edward Schmerling, Ali-akbar Agha-mohammadi +1
In this paper we present the PUMP (Parallel Uncertainty-aware Multiobjective Planning) algorithm for addressing the stochastic kinodynamic motion planning problem, whereby one seek…
Optimal Sampling-Based Motion Planning under Differential Constraints: the Driftless Case
Edward Schmerling, Lucas Janson, Marco Pavone
Motion planning under differential constraints is a classic problem in robotics. To date, the state of the art is represented by sampling-based techniques, with the Rapidly-explori…