5 papers
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…
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…
iMTSP: Solving Min-Max Multiple Traveling Salesman Problem with Imperative Learning
Yifan Guo, Zhongqiang Ren, Chen Wang
This paper considers a Min-Max Multiple Traveling Salesman Problem (MTSP), where the goal is to find a set of tours, one for each agent, to collectively visit all the cities while…