51 citations · 140 across the 19 of their papers we have counts for
19 papers
Platooning Connected, Autonomous, and Human-Driven Vehicles: A Deep Reinforcement Learning-based Approach
Zhen Qina, Dong-Fan Xie, Heng Ma +2
Conventionally, existing vehicle platooning approaches are designed for connected vehicles, typically including connected autonomous vehicles and connected human-driven vehicles. N…
CMP: Cooperative Motion Prediction with Multi-Agent Communication
Zehao Wang, Yuping Wang, Zhuoyuan Wu +4
The confluence of the advancement of Autonomous Vehicles (AVs) and the maturity of Vehicle-to-Everything (V2X) communication has enabled the capability of cooperative connected and…
Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation
Jiachen Li, Chuanbo Hua, Jianpeng Yao +4
Social robot navigation can be helpful in various contexts of daily life but requires safe human-robot interactions and efficient trajectory planning. While modeling pairwise relat…
SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task Execution
Zhixuan Liang, Yao Mu, Hengbo Ma +3
Diffusion models have demonstrated strong potential for robotic trajectory planning. However, generating coherent trajectories from high-level instructions remains challenging, esp…
Learning Physical Dynamics with Subequivariant Graph Neural Networks
Jiaqi Han, Wenbing Huang, Hengbo Ma +3
Graph Neural Networks (GNNs) have become a prevailing tool for learning physical dynamics. However, they still encounter several challenges: 1) Physical laws abide by symmetry, whi…
EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction
Jiachen Li, Chuanbo Hua, Jinkyoo Park +3
While the modeling of pair-wise relations has been widely studied in multi-agent interacting systems, its ability to capture higher-level and larger-scale group-wise activities is…
Important Object Identification with Semi-Supervised Learning for Autonomous Driving
Jiachen Li, Haiming Gang, Hengbo Ma +2
Accurate identification of important objects in the scene is a prerequisite for safe and high-quality decision making and motion planning of intelligent agents (e.g., autonomous ve…
Learning Differentiable Safety-Critical Control using Control Barrier Functions for Generalization to Novel Environments
Hengbo Ma, Bike Zhang, Masayoshi Tomizuka +1
Control barrier functions (CBFs) have become a popular tool to enforce safety of a control system. CBFs are commonly utilized in a quadratic program formulation (CBF-QP) as safety-…
Cross Domain Robot Imitation with Invariant Representation
Zhao-Heng Yin, Lingfeng Sun, Hengbo Ma +2
Animals are able to imitate each others' behavior, despite their difference in biomechanics. In contrast, imitating the other similar robots is a much more challenging task in robo…
RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecasting
Jiachen Li, Fan Yang, Hengbo Ma +3
Motion forecasting plays a significant role in various domains (e.g., autonomous driving, human-robot interaction), which aims to predict future motion sequences given a set of his…
Spectral Temporal Graph Neural Network for Trajectory Prediction
Defu Cao, Jiachen Li, Hengbo Ma +1
An effective understanding of the contextual environment and accurate motion forecasting of surrounding agents is crucial for the development of autonomous vehicles and social mobi…
Speed Planning Using Bezier Polynomials with Trapezoidal Corridors
Jialun Li, Xiaojia Xie, Hengbo Ma +2
To generate safe and real-time trajectories for an autonomous vehicle in dynamic environments, path and speed decoupled planning methods are often considered. This paper studies sp…
Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking
Jiachen Li, Hengbo Ma, Zhihao Zhang +2
An effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are indispensable for intelligent mobile systems (e.g. autonomous…
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…
Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network
Jiachen Li, Hengbo Ma, Zhihao Zhang +1
Effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are indispensable for intelligent mobile systems (like autonomous veh…
Coordination and Trajectory Prediction for Vehicle Interactions via Bayesian Generative Modeling
Jiachen Li, Hengbo Ma, Wei Zhan +1
Coordination recognition and subtle pattern prediction of future trajectories play a significant role when modeling interactive behaviors of multiple agents. Due to the essential p…
Conditional Generative Neural System for Probabilistic Trajectory Prediction
Jiachen Li, Hengbo Ma, Masayoshi Tomizuka
Effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are critical for intelligent systems such as autonomous vehicles and…
Interaction-aware Multi-agent Tracking and Probabilistic Behavior Prediction via Adversarial Learning
Jiachen Li, Hengbo Ma, Masayoshi Tomizuka
In order to enable high-quality decision making and motion planning of intelligent systems such as robotics and autonomous vehicles, accurate probabilistic predictions for surround…
Generic Probabilistic Interactive Situation Recognition and Prediction: From Virtual to Real
Jiachen Li, Hengbo Ma, Wei Zhan +1
Accurate and robust recognition and prediction of traffic situation plays an important role in autonomous driving, which is a prerequisite for risk assessment and effective decisio…