6 papers
Unified Prediction and Planning via Conflict-Aware Disjoint Parameter Training
Taewon Seo, Seonae Jeon, Giwon Lee +2
Accurate motion prediction of surrounding agents and safe motion planning are two closely coupled key tasks for social robot navigation in crowded environments. Deploying these sys…
HEAT: Heterogeneous End-to-End Autonomous Driving via Trajectory-Guided World Models
Hoonhee Cho, Giwon Lee, Jae-Young Kang +3
End-to-end autonomous driving has emerged as a compelling alternative to traditional modular pipelines by directly mapping raw sensor data to driving actions. While recent approach…
VR-Drive: Viewpoint-Robust End-to-End Driving with Feed-Forward 3D Gaussian Splatting
Hoonhee Cho, Jae-Young Kang, Giwon Lee +4
End-to-end autonomous driving (E2E-AD) has emerged as a promising paradigm that unifies perception, prediction, and planning into a holistic, data-driven framework. However, achiev…
Interaction-Merged Motion Planning: Effectively Leveraging Diverse Motion Datasets for Robust Planning
Giwon Lee, Wooseong Jeong, Daehee Park +2
Motion planning is a crucial component of autonomous robot driving. While various trajectory datasets exist, effectively utilizing them for a target domain remains challenging due…
Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning
Giwon Lee, Daehee Park, Jaewoo Jeong +1
Safe and effective motion planning is crucial for autonomous robots. Diffusion models excel at capturing complex agent interactions, a fundamental aspect of decision-making in dyna…
Multi-modal Knowledge Distillation-based Human Trajectory Forecasting
Jaewoo Jeong, Seohee Lee, Daehee Park +2
Pedestrian trajectory forecasting is crucial in various applications such as autonomous driving and mobile robot navigation. In such applications, camera-based perception enables t…