8 papers
Flying to Image-Specified Objects: 3D Quadrotor Navigation via Cross-Graph Memory and Viewpoint Planning
Junjie Gao, Yuqi Chen, Yongzhou Pan +3
Instance-Specific Image-Goal Navigation (InstanceImageNav) requires a robot to navigate toward the exact object instance depicted in a query image. Extending this task to quadrotor…
TRUST-UP: Trustworthy Reinforcement learning Using Safe Techniques for UAV Pursuit
Yaosheng Deng, Mengtao Lyu, Junjie Gao +2
Reinforcement Learning (RL) enables autonomous aerial vehicles to adapt quickly and make efficient decisions, making it well-suited for dynamic urban air mobility operations. Howev…
GaussFly: Contrastive Reinforcement Learning for Visuomotor Policies in 3D Gaussian Fields
Yuhang Zhang, Mingsheng Li, Yujing Shang +4
Learning visuomotor policies for Autonomous Aerial Vehicles (AAVs) relying solely on monocular vision is an attractive yet highly challenging paradigm. Existing end-to-end learning…
Learning Adaptive Cross-Embodiment Visuomotor Policy with Contrastive Prompt Orchestration
Yuhang Zhang, Chao Yan, Jiaxi Yu +2
Learning adaptive visuomotor policies for embodied agents remains a formidable challenge, particularly when facing cross-embodiment variations such as diverse sensor configurations…
Oracle-Guided Masked Contrastive Reinforcement Learning for Visuomotor Policies
Yuhang Zhang, Jiaping Xiao, Chao Yan +1
A prevailing approach for learning visuomotor policies is to employ reinforcement learning to map high-dimensional visual observations directly to action commands. However, the com…
ReviBranch: Deep Reinforcement Learning for Branch-and-Bound with Revived Trajectories
Dou Jiabao, Nie Jiayi, Yihang Cheng +5
The Branch-and-bound (B&B) algorithm is the main solver for Mixed Integer Linear Programs (MILPs), where the selection of branching variable is essential to computational efficienc…