activity
20242026
most citedHEIGHT: Heterogeneous Interaction Graph Transformer for Robot Navigation in Crowded and Constrained Environments

9 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2026

Rethinking Gaussian Trajectory Predictors: Calibrated Uncertainty for Safe Planning

Fatemeh Cheraghi Pouria, Mahsa Golchoubian, Katherine Driggs-Campbell

Accurate trajectory prediction is critical for safe autonomous navigation in crowded environments. While many trajectory predictors output Gaussian distributions to represent the m…

cs.RO2025

Hierarchical Intention Tracking with Switching Trees for Real-Time Adaptation to Dynamic Human Intentions during Collaboration

Zhe Huang, Ye-Ji Mun, Fatemeh Cheraghi Pouria +1

During collaborative tasks, human behavior is guided by multiple levels of intentions that evolve over time, such as task sequence preferences and interaction strategies. To adapt…

cs.RO2025

Interaction-aware Conformal Prediction for Crowd Navigation

Zhe Huang, Tianchen Ji, Heling Zhang +3

During crowd navigation, robot motion plan needs to consider human motion uncertainty, and the human motion uncertainty is dependent on the robot motion plan. We introduce Interact…

cs.RO2024★ 9 cited

HEIGHT: Heterogeneous Interaction Graph Transformer for Robot Navigation in Crowded and Constrained Environments

Shuijing Liu, Haochen Xia, Fatemeh Cheraghi Pouria +5

We study the problem of robot navigation in dense and interactive crowds with static constraints such as corridors and furniture. Previous methods fail to consider all types of spa…

cs.RO2024

Topology-Guided ORCA: Smooth Multi-Agent Motion Planning in Constrained Environments

Fatemeh Cheraghi Pouria, Zhe Huang, Ananya Yammanuru +2

We present Topology-Guided ORCA as an alternative simulator to replace ORCA for planning smooth multi-agent motions in environments with static obstacles. Despite the impressive pe…