12 citations · 19 across the 8 of their papers we have counts for
10 papers
Point-Level Refinable Semantic Mapping for Spatial Understanding
Taimeng Fu, Yi Du, Zitong Zhan +4
Open-vocabulary 3D semantic maps have emerged as a key spatial memory representation for long-horizon robot autonomy, enabling robots to reason about objects, their spatial relatio…
Neuro-Symbolic Learning for Long-Horizon Task Planning Under Complex Logical Constraints
Qiwei Du, Zitong Zhan, Shaoshu Su +7
Task planning often suffers from severe efficiency bottlenecks when robots must reason over long-horizon action sequences under complex logical constraints, including object afford…
Learning When to Jump for Off-road Navigation
Zhipeng Zhao, Taimeng Fu, Shaoshu Su +5
Low speed does not always guarantee safety in off-road driving. For instance, crossing a ditch may be risky at a low speed due to the risk of getting stuck, yet safe at a higher sp…
Vision-Language Memory for Spatial Reasoning
Zuntao Liu, Yi Du, Taimeng Fu +3
Spatial reasoning is a critical capability for intelligent robots, yet current vision-language models (VLMs) still fall short of human-level performance in video-based spatial reas…
Fast Task Planning with Neuro-Symbolic Relaxation
Qiwei Du, Bowen Li, Yi Du +5
Real-world task planning requires long-horizon reasoning over large sets of objects with complex relationships and attributes, leading to a combinatorial explosion for classical sy…
VL-Nav: Neuro-Symbolic Reasoning-based Vision-Language Navigation
Yi Du, Taimeng Fu, Zhipeng Zhao +6
Navigating unseen, large-scale environments based on complex and abstract human instructions remains a formidable challenge for autonomous mobile robots. Addressing this requires r…
AnyNav: Visual Neuro-Symbolic Friction Learning for Off-road Navigation
Taimeng Fu, Zitong Zhan, Zhipeng Zhao +7
Off-road navigation is critical for a wide range of field robotics applications from planetary exploration to disaster response. However, it remains a longstanding challenge due to…
iWalker: Imperative Visual Planning for Walking Humanoid Robot
Xiao Lin, Yuhao Huang, Taimeng Fu +2
Humanoid robots, designed to operate in human-centric environments, serve as a fundamental platform for a broad range of tasks. Although humanoid robots have been extensively studi…
Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy
Chen Wang, Kaiyi Ji, Junyi Geng +16
Data-driven methods such as reinforcement and imitation learning have achieved remarkable success in robot autonomy. However, their data-centric nature still hinders them from gene…
PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving
Zhipeng Zhao, Bowen Li, Yi Du +2
Motion prediction is critical for autonomous off-road driving, however, it presents significantly more challenges than on-road driving because of the complex interaction between th…