52 citations · 75 across the 6 of their papers we have counts for
6 papers
DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba
Chengran Yuan, Zhanqi Zhang, Jiawei Sun +8
Motion planning is a challenging task to generate safe and feasible trajectories in highly dynamic and complex environments, forming a core capability for autonomous vehicles. In t…
ControlMTR: Control-Guided Motion Transformer with Scene-Compliant Intention Points for Feasible Motion Prediction
Jiawei Sun, Chengran Yuan, Shuo Sun +7
The ability to accurately predict feasible multimodal future trajectories of surrounding traffic participants is crucial for behavior planning in autonomous vehicles. The Motion Tr…
GET-DIPP: Graph-Embedded Transformer for Differentiable Integrated Prediction and Planning
Jiawei Sun, Chengran Yuan, Shuo Sun +5
Accurately predicting interactive road agents' future trajectories and planning a socially compliant and human-like trajectory accordingly are important for autonomous vehicles. In…
GloCAL: Glocalized Curriculum-Aided Learning of Multiple Tasks with Application to Robotic Grasping
Anil Kurkcu, Cihan Acar, Domenico Campolo +1
The domain of robotics is challenging to apply deep reinforcement learning due to the need for large amounts of data and for ensuring safety during learning. Curriculum learning ha…
Approximating Constraint Manifolds Using Generative Models for Sampling-Based Constrained Motion Planning
Cihan Acar, Keng Peng Tee
Sampling-based motion planning under task constraints is challenging because the null-measure constraint manifold in the configuration space makes rejection sampling extremely inef…
KOVIS: Keypoint-based Visual Servoing with Zero-Shot Sim-to-Real Transfer for Robotics Manipulation
En Yen Puang, Keng Peng Tee, Wei Jing
We present KOVIS, a novel learning-based, calibration-free visual servoing method for fine robotic manipulation tasks with eye-in-hand stereo camera system. We train the deep neura…