354 citations · 526 across the 23 of their papers we have counts for
36 papers
Expressing Diverse Human Driving Behavior with Probabilistic Rewards and Online Inference
Liting Sun, Zheng Wu, Hengbo Ma +1
In human-robot interaction (HRI) systems, such as autonomous vehicles, understanding and representing human behavior are important. Human behavior is naturally rich and diverse. Co…
Data-Driven Multi-Objective Controller Optimization for a Magnetically-Levitated Nanopositioning System
Xiaocong Li, Haiyue Zhu, Jun Ma +4
The performance achieved with traditional model-based control system design approaches typically relies heavily upon accurate modeling of the motion dynamics. However, modeling the…
Efficient Sampling-Based Maximum Entropy Inverse Reinforcement Learning with Application to Autonomous Driving
Zheng Wu, Liting Sun, Wei Zhan +2
In the past decades, we have witnessed significant progress in the domain of autonomous driving. Advanced techniques based on optimization and reinforcement learning (RL) become in…
Towards Better Performance and More Explainable Uncertainty for 3D Object Detection of Autonomous Vehicles
Hujie Pan, Zining Wang, Wei Zhan +1
In this paper, we propose a novel form of the loss function to increase the performance of LiDAR-based 3d object detection and obtain more explainable and convincing uncertainty fo…
Guided Policy Search Model-based Reinforcement Learning for Urban Autonomous Driving
Zhuo Xu, Jianyu Chen, Masayoshi Tomizuka
In this paper, we continue our prior work on using imitation learning (IL) and model free reinforcement learning (RL) to learn driving policies for autonomous driving in urban scen…
Cascade Attribute Network: Decomposing Reinforcement Learning Control Policies using Hierarchical Neural Networks
Haonan Chang, Zhuo Xu, Masayoshi Tomizuka
Reinforcement learning methods have been developed to achieve great success in training control policies in various automation tasks. However, a main challenge of the wider applica…