activity
20182022
most citedCooperative Task and Motion Planning for Multi-Arm Assembly Systems

20 citations · 48 across the 21 of their papers we have counts for

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20 papers · 1 filter

cs.RO20221 cited

P4P: Conflict-Aware Motion Prediction for Planning in Autonomous Driving

Qiao Sun, Xin Huang, Brian C. Williams +1

Motion prediction is crucial in enabling safe motion planning for autonomous vehicles in interactive scenarios. It allows the planner to identify potential conflicts with other tra…

cs.RO2022

InterSim: Interactive Traffic Simulation via Explicit Relation Modeling

Qiao Sun, Xin Huang, Brian C. Williams +1

Interactive traffic simulation is crucial to autonomous driving systems by enabling testing for planners in a more scalable and safe way compared to real-world road testing. Existi…

cs.RO20224 cited

M2I: From Factored Marginal Trajectory Prediction to Interactive Prediction

Qiao Sun, Xin Huang, Junru Gu +2

Predicting future motions of road participants is an important task for driving autonomously in urban scenes. Existing models excel at predicting marginal trajectories for single a…

cs.RO2022

Non-Gaussian Risk Bounded Trajectory Optimization for Stochastic Nonlinear Systems in Uncertain Environments

Weiqiao Han, Ashkan Jasour, Brian Williams

We address the risk bounded trajectory optimization problem of stochastic nonlinear robotic systems. More precisely, we consider the motion planning problem in which the robot has…

cs.RO202220 cited

Cooperative Task and Motion Planning for Multi-Arm Assembly Systems

Jingkai Chen, Jiaoyang Li, Yijiang Huang +7

Multi-robot assembly systems are becoming increasingly appealing in manufacturing due to their ability to automatically, flexibly, and quickly construct desired structural designs.…

cs.RO2021

HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling

Xin Huang, Guy Rosman, Igor Gilitschenski +4

Modeling multi-modal high-level intent is important for ensuring diversity in trajectory prediction. Existing approaches explore the discrete nature of human intent before predicti…