12 papers
Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation
Junjin Xiao, Dongyang Li, Yandan Yang +9
This paper tackles spatial perception and manipulation challenges in Vision-Language-Action (VLA) models. To address depth ambiguity from monocular input, we leverage a pre-trained…
ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning
Yandan Yang, Shuang Zeng, Tong Lin +11
Building general-purpose embodied agents across diverse hardware remains a central challenge in robotics, often framed as the ''one-brain, many-forms'' paradigm. Progress is hinder…
MerNav: A Highly Generalizable Memory-Execute-Review Framework for Zero-Shot Object Goal Navigation
Dekang Qi, Shuang Zeng, Xinyuan Chang +4
Visual Language Navigation (VLN) is one of the fundamental capabilities for embodied intelligence and a critical challenge that urgently needs to be addressed. However, existing me…
ABot-PhysWorld: Interactive World Foundation Model for Robotic Manipulation with Physics Alignment
Yuzhi Chen, Ronghan Chen, Dongjie Huo +11
Video-based world models offer a powerful paradigm for embodied simulation and planning, yet state-of-the-art models often generate physically implausible manipulations - such as o…
Persistent Autoregressive Mapping with Traffic Rules for Autonomous Driving
Shiyi Liang, Xinyuan Chang, Changjie Wu +8
Safe autonomous driving requires both accurate HD map construction and persistent awareness of traffic rules, even when their associated signs are no longer visible. However, exist…
MindDriver: Introducing Progressive Multimodal Reasoning for Autonomous Driving
Lingjun Zhang, Yujian Yuan, Changjie Wu +7
Vision-Language Models (VLM) exhibit strong reasoning capabilities, showing promise for end-to-end autonomous driving systems. Chain-of-Thought (CoT), as VLM's widely used reasonin…