8 citations · 11 across the 2 of their papers we have counts for
6 papers
Simulating Autonomous Driving in Massive Mixed Urban Traffic
Yuanfu Luo, Panpan Cai, Yiyuan Lee +1
Autonomous driving in an unregulated urban crowd is an outstanding challenge, especially, in the presence of many aggressive, high-speed traffic participants. This paper presents S…
MAGIC: Learning Macro-Actions for Online POMDP Planning
Yiyuan Lee, Panpan Cai, David Hsu
The partially observable Markov decision process (POMDP) is a principled general framework for robot decision making under uncertainty, but POMDP planning suffers from high computa…
SUMMIT: A Simulator for Urban Driving in Massive Mixed Traffic
Panpan Cai, Yiyuan Lee, Yuanfu Luo +1
Autonomous driving in an unregulated urban crowd is an outstanding challenge, especially, in the presence of many aggressive, high-speed traffic participants. This paper presents S…
LeTS-Drive: Driving in a Crowd by Learning from Tree Search
Panpan Cai, Yuanfu Luo, Aseem Saxena +2
Autonomous driving in a crowded environment, e.g., a busy traffic intersection, is an unsolved challenge for robotics. The robot vehicle must contend with a dynamic and partially o…
PORCA: Modeling and Planning for Autonomous Driving among Many Pedestrians
Yuanfu Luo, Panpan Cai, Aniket Bera +3
This paper presents a planning system for autonomous driving among many pedestrians. A key ingredient of our approach is PORCA, a pedestrian motion prediction model that accounts f…
HyP-DESPOT: A Hybrid Parallel Algorithm for Online Planning under Uncertainty
Panpan Cai, Yuanfu Luo, David Hsu +1
Planning under uncertainty is critical for robust robot performance in uncertain, dynamic environments, but it incurs high computational cost. State-of-the-art online search algori…