1.1k citations · 1.3k across the 29 of their papers we have counts for
8 papers · 1 filter
Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving
Haohong Lin, Wenhao Ding, Zuxin Liu +4
In the domain of autonomous driving, the offline Reinforcement Learning~(RL) approaches exhibit notable efficacy in addressing sequential decision-making problems from offline data…
Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization
Fan Yang, Wenxuan Zhou, Zuxin Liu +2
Safe Reinforcement Learning (RL) plays an important role in applying RL algorithms to safety-critical real-world applications, addressing the trade-off between maximizing rewards a…
Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving
Ye Li, Hanjiang Hu, Zuxin Liu +3
Cameras and LiDARs are both important sensors for autonomous driving, playing critical roles in 3D object detection. Camera-LiDAR Fusion has been a prevalent solution for robust an…
SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles
Chejian Xu, Wenhao Ding, Weijie Lyu +6
As shown by recent studies, machine intelligence-enabled systems are vulnerable to test cases resulting from either adversarial manipulation or natural distribution shifts. This ha…
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving
Hanjiang Hu, Zuxin Liu, Sharad Chitlangia +2
The past few years have witnessed an increasing interest in improving the perception performance of LiDARs on autonomous vehicles. While most of the existing works focus on develop…
MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments
Zuxin Liu, Baiming Chen, Hongyi Zhou +3
Multi-agent navigation in dynamic environments is of great industrial value when deploying a large scale fleet of robot to real-world applications. This paper proposes a decentrali…
DS-SLAM: A Semantic Visual SLAM towards Dynamic Environments
Chao Yu, Zuxin Liu, Xinjun Liu +4
Simultaneous Localization and Mapping (SLAM) is considered to be a fundamental capability for intelligent mobile robots. Over the past decades, many impressed SLAM systems have bee…
Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach
Zuxin Liu, Mansur Arief, Ding Zhao
Autonomous vehicle manufacturers recognize that LiDAR provides accurate 3D views and precise distance measures under highly uncertain driving conditions. Its practical implementati…