12 citations · 25 across the 9 of their papers we have counts for
9 papers · 1 filter
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…
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…
iKap: Kinematics-aware Planning with Imperative Learning
Qihang Li, Zhuoqun Chen, Haoze Zheng +5
Trajectory planning in robotics aims to generate collision-free pose sequences that can be reliably executed. Recently, vision-to-planning systems have gained increasing attention…
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…
PyPose v0.6: The Imperative Programming Interface for Robotics
Zitong Zhan, Xiangfu Li, Qihang Li +33
PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has…