Publications (5)
AION: Aerial Indoor Object-Goal Navigation Using Dual-Policy Reinforcement Learning
Zichen Yan, Yuchen Hou, Shenao Wang +3
Object-Goal Navigation (ObjectNav) requires an agent to autonomously explore an unknown environment and navigate toward target objects specified by a semantic label. While prior wo…
FOSP: Fine-tuning Offline Safe Policy through World Models
Chenyang Cao, Yucheng Xin, Silang Wu +4
Offline Safe Reinforcement Learning (RL) seeks to address safety constraints by learning from static datasets and restricting exploration. However, these approaches heavily rely on…
Offline Goal-Conditioned Reinforcement Learning for Safety-Critical Tasks with Recovery Policy
Chenyang Cao, Zichen Yan, Renhao Lu +2
Offline goal-conditioned reinforcement learning (GCRL) aims at solving goal-reaching tasks with sparse rewards from an offline dataset. While prior work has demonstrated various ap…
Safety Correction from Baseline: Towards the Risk-aware Policy in Robotics via Dual-agent Reinforcement Learning
Linrui Zhang, Zichen Yan, Li Shen +3
Learning a risk-aware policy is essential but rather challenging in unstructured robotic tasks. Safe reinforcement learning methods open up new possibilities to tackle this problem…
SIGN: Safety-Aware Image-Goal Navigation for Autonomous Drones via Reinforcement Learning
Zichen Yan, Rui Huang, Lei He +2
Image-goal navigation (ImageNav) tasks a robot with autonomously exploring an unknown environment and reaching a location that visually matches a given target image. While prior wo…