2 citations · 10 across the 17 of their papers we have counts for
8 papers · 1 filter
Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
Zhihua Hua, Junli Wang, Pengfei LI +6
Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental results indicate that many end-to-en…
Agentic Self-Evolutionary Replanning for Embodied Navigation
Guoliang Li, Ruihua Han, Chengyang Li +5
Failure is inevitable for embodied navigation in complex environments. To enhance the resilience, replanning (RP) is a viable option, where the robot is allowed to fail, but is cap…
Drive in Corridors: Enhancing the Safety of End-to-end Autonomous Driving via Corridor Learning and Planning
Zhiwei Zhang, Ruichen Yang, Ke Wu +5
Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a…
Topology-Driven Trajectory Optimization for Modelling Controllable Interactions Within Multi-Vehicle Scenario
Changjia Ma, Yi Zhao, Zhongxue Gan +2
Trajectory optimization in multi-vehicle scenarios faces challenges due to its non-linear, non-convex properties and sensitivity to initial values, making interactions between vehi…
VINGS-Mono: Visual-Inertial Gaussian Splatting Monocular SLAM in Large Scenes
Ke Wu, Zicheng Zhang, Muer Tie +3
VINGS-Mono is a monocular (inertial) Gaussian Splatting (GS) SLAM framework designed for large scenes. The framework comprises four main components: VIO Front End, 2D Gaussian Map,…
Planning by Simulation: Motion Planning with Learning-based Parallel Scenario Prediction for Autonomous Driving
Tian Niu, Kaizhao Zhang, Zhongxue Gan +1
Planning safe trajectories for autonomous vehicles is essential for operational safety but remains extremely challenging due to the complex interactions among traffic participants.…