51 citations · 140 across the 19 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…
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…
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…
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…