Safe POMDP Online Planning Among Dynamic Agents via Adaptive Conformal Prediction

Online planning for partially observable Markov decision processes (POMDPs) provides efficient techniques for robot decision-making under uncertainty. However, existing methods fall short of preventing safety violations in dynamic environments. This letter presents a novel safe POMDP online planning...

Full description

Saved in:
Bibliographic Details
Published in:IEEE robotics and automation letters 2024-11, Vol.9 (11), p.9946-9953
Main Authors: Sheng, Shili, Yu, Pian, Parker, David, Kwiatkowska, Marta, Feng, Lu
Format: Article
Language:English
Subjects:
AI-enabled robotics
Artificial intelligence
Formal methods in robotics and automation
Heuristic algorithms
Markov processes
Pedestrians
Planning
planning under uncertainty
Prediction models
robot safety
Robotics and automation
Safety
Trajectory
Trajectory planning
Uncertainty
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!