12 papers · 1 filter
What Matters for Latent Actions in Robot Learning
Xizhou Bu, Qingda Hu, Lei Zhou +13
Latent Action Models (LAMs) have emerged as a promising paradigm for enabling robot learning to leverage large-scale unlabeled videos through latent actions that serve as compact s…
FutureNav: Unified World-Action Modeling for Vision-and-Language Navigation
Lingfeng Zhang, Zeying Gong, Xiaoshuai Hao +7
Vision-and-language navigation (VLN) in continuous environments requires an agent to ground instructions in egocentric observations while maintaining spatial understanding across l…
OneVLA: A Unified Framework for Embodied Tasks
Lingfeng Zhang, Xiaoshuai Hao, Yingbo Tang +10
Navigation and manipulation are fundamental capabilities of embodied intelligence, enabling robots to interpret natural language commands and interact physically with their surroun…
Beyond Binary Success: A Diagnostic Meta-Evaluation Framework for Fine-Grained Manipulation
He-Yang Xu, Pengyuan Zhang, Zongyuan Ge +5
Fine-grained manipulation marks a regime where global scene context no longer suffices, and success hinges on the tight coupling of local attribute grounding, high-fidelity spatial…
Data-Asymmetric Latent Imagination and Reranking for 3D Robotic Imitation Learning
Lianghao Luo, Xizhou Bu, Ruyan Liu +5
Robotic imitation learning typically assumes access to optimal demonstrations, yet real-world data collection often yields suboptimal, exploratory, or even failed trajectories. Dis…
Walk With Me: Long-Horizon Social Navigation for Human-Centric Outdoor Assistance
Lingfeng Zhang, Xiaoshuai Hao, Xizhou Bu +11
Assisting humans in open-world outdoor environments requires robots to translate high-level natural-language intentions into safe, long-horizon, and socially compliant navigation b…
SocialNav-Map: Dynamic Mapping with Human Trajectory Prediction for Zero-Shot Social Navigation
Lingfeng Zhang, Erjia Xiao, Xiaoshuai Hao +7
Social navigation in densely populated dynamic environments poses a significant challenge for autonomous mobile robots, requiring advanced strategies for safe interaction. Existing…
RoboAfford++: A Generative AI-Enhanced Dataset for Multimodal Affordance Learning in Robotic Manipulation and Navigation
Xiaoshuai Hao, Yingbo Tang, Lingfeng Zhang +6
Robotic manipulation and navigation are fundamental capabilities of embodied intelligence, enabling effective robot interactions with the physical world. Achieving these capabiliti…
Learning to Navigate Socially Through Proactive Risk Perception
Erjia Xiao, Lingfeng Zhang, Yingbo Tang +7
In this report, we describe the technical details of our submission to the IROS 2025 RoboSense Challenge Social Navigation Track. This track focuses on developing RGBD-based percep…
Team Xiaomi EV-AD VLA: Caption-Guided Retrieval System for Cross-Modal Drone Navigation -- Technical Report for IROS 2025 RoboSense Challenge Track 4
Lingfeng Zhang, Erjia Xiao, Yuchen Zhang +7
Cross-modal drone navigation remains a challenging task in robotics, requiring efficient retrieval of relevant images from large-scale databases based on natural language descripti…
MiMo-Embodied: X-Embodied Foundation Model Technical Report
Xiaoshuai Hao, Lei Zhou, Zhijian Huang +41
We open-source MiMo-Embodied, the first cross-embodied foundation model to successfully integrate and achieve state-of-the-art performance in both Autonomous Driving and Embodied A…
DSBench: A Comprehensive Benchmark for Evaluating External and In-Cabin Risks
Xianhui Meng, Yuchen Zhang, Zhijian Huang +12
Vision-Language Models (VLMs) show great promise for autonomous driving, but their suitability for safety-critical scenarios is largely unexplored, raising safety concerns. This is…