7 papers · 1 filter
Retrospective Open-Vocabulary Memory for Long-Term Object Search
Jiaming Wang, Zhiwei Xue, Chen Jizhuo +2
Long-term object search requires learning where objects usually appear from repeated but uneven observations of a changing environment. We formulate retrospective open-vocabulary m…
Learning Social Navigation from Internet Videos in the Policy State Space
Jiaming Wang, Duc Thang Nguyen, Jizhuo Chen +4
Training robust social-navigation policies requires simulators with diverse scene layouts, terrain, and human motion, but constructing such environments and specifying pedestrian b…
How to Better Train VLAs: Lessons Learned From the REAL-I Challenge at ICRA 2026
Jiaming Wang, Jizhuo Chen, Diwen Liu +11
How can robot policies learn more effectively from a fixed demonstration budget? The first Real-world Embodied AI Learning (REAL-I) Challenge at ICRA 2026 examined this question th…
Change-Robust Online Topological Memory for Long-Term Relocalization and Semantic Navigation
Jiaming Wang, Jizhuo Chen, Diwen Liu +4
Long-term semantic navigation requires a robot to reuse past observations after appearance and scene change, but semantic memories are only useful if the robot can relocalize into…
GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning
Jizhuo Chen, Diwen Liu, Jiaming Wang +1
GBPP is a fast learning based scorer that selects a robot base pose for grasping from a single RGB-D snapshot. The method uses a two stage curriculum: (1) a simple distance-visibil…
GeNIE: A Generalizable Navigation System for In-the-Wild Environments
Jiaming Wang, Diwen Liu, Jizhuo Chen +4
Reliable navigation in unstructured, real-world environments remains a significant challenge for embodied agents, especially when operating across diverse terrains, weather conditi…
Probable Object Location (POLo) Score Estimation for Efficient Object Goal Navigation
Jiaming Wang, Harold Soh
To advance the field of autonomous robotics, particularly in object search tasks within unexplored environments, we introduce a novel framework centered around the Probable Object…