6 papers
Learning Positive-Incentive Point Sampling in Neural Implicit Fields for Object Pose Estimation
Yifei Shi, Boyan Wan, Xin Xu +1
Learning neural implicit fields of 3D shapes is a rapidly emerging field that enables shape representation at arbitrary resolutions. Due to the flexibility, neural implicit fields…
How Far Can We Go with Pixels Alone? A Pilot Study on Screen-Only Navigation in Commercial 3D ARPGs
Kaijie Xu, Mustafa Bugti, Clark Verbrugge
Modern 3D game levels rely heavily on visual guidance, yet the navigability of level layouts remains difficult to quantify. Prior work either simulates play in simplified environme…
(Perlin) Noise as AI coordinator
Kaijie Xu, Clark Verbrugge
Large scale control of nonplayer agents is central to modern games, while production systems still struggle to balance several competing goals: locally smooth, natural behavior, an…
High Dimensional Procedural Content Generation
Kaijie Xu, Clark Verbrugge
Procedural content generation (PCG) has made substantial progress in shaping static 2D/3D geometry, while most methods treat gameplay mechanics as auxiliary and optimize only over…
CogNav: Cognitive Process Modeling for Object Goal Navigation with LLMs
Yihan Cao, Jiazhao Zhang, Zhinan Yu +5
Object goal navigation (ObjectNav) is a fundamental task in embodied AI, requiring an agent to locate a target object in previously unseen environments. This task is particularly c…
PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation
Wenxuan Li, Hang Zhao, Zhiyuan Yu +4
While non-prehensile manipulation (e.g., controlled pushing/poking) constitutes a foundational robotic skill, its learning remains challenging due to the high sensitivity to comple…